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https://api.github.com/repos/huggingface/datasets/issues/8714 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8714/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8714/comments | https://api.github.com/repos/huggingface/datasets/issues/8714/events | https://github.com/huggingface/datasets/issues/8714 | 5,647,821,325 | I_kwDODunzps8AAAABUKLqDQ | 8,714 | Casting mixed JSON and plain strings to Json depends on row order and batch size | {
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"#self-assign\n\nI have reproduced this on current main and prepared a focused fix using the existing per-value encoding rule, with regression tests for both row orders and multiple batch sizes."
] | 2026-09-30 14:11:42 | 2026-09-30 14:12:11 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
Casting a string column containing both JSON-encoded values and plain strings to `Json()` gives different results depending on row order and `batch_size`. A plain string among the first five rows makes valid JSON values decode as strings; a plain string after those rows is left unencoded and raise... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8709 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8709/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8709/comments | https://api.github.com/repos/huggingface/datasets/issues/8709/events | https://github.com/huggingface/datasets/issues/8709 | 5,627,431,520 | I_kwDODunzps8AAAABT2vKYA | 8,709 | string_to_dict maps fields to unrelated regex capture groups | {
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{
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"#self-assign"
] | 2026-09-29 08:17:13 | 2026-09-29 08:19:03 | null | {
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"followers_url": "https://api.github.c... | NONE | [] | null | null | null | null | ## Problem
`string_to_dict` creates named groups for format fields, but builds the result by zipping field names with every regex capture. An unrelated capturing group shifts the values.
## Reproduction
```python
from datasets.utils.py_utils import string_to_dict
print(string_to_dict("train/alice", "(train|test)/{na... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8675 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8675/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8675/comments | https://api.github.com/repos/huggingface/datasets/issues/8675/events | https://github.com/huggingface/datasets/issues/8675 | 5,560,824,749 | I_kwDODunzps8AAAABS3NzrQ | 8,675 | load_dataset("json") fails on mixed-shape JSONL when a chunksize boundary separates the shapes | {
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"Hi, I'd like to work on this issue.\n\nI'll first reproduce the failure with a focused test, then investigate how schemas are inferred and aligned across JSONL chunks in `Json._generate_tables`.\n\nMy initial approach is to make chunked loading consistent with single-chunk loading by unifying the columns and filli... | 2026-09-23 23:31:51 | 2026-09-24 00:46:12 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
`load_dataset("json")` raises `DatasetGenerationError` ("column names don't match") on a valid JSONL file that mixes two record shapes, whenever the default 10MB `chunksize` splits the file so that different chunks see different sets of columns.
The JSON loader reads the file in `chunksize` batch... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8637 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8637/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8637/comments | https://api.github.com/repos/huggingface/datasets/issues/8637/events | https://github.com/huggingface/datasets/issues/8637 | 5,492,155,234 | I_kwDODunzps8AAAABR1ujYg | 8,637 | FileLock wrapper drops timeout and every other constructor argument | {
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"Correction to the environment section above, found while testing a change that touches this wrapper.\n\nThis is filelock-version dependent, and filelock 4.0.0 already fixes it. Same probe, same `datasets` commit, only the filelock version differing:\n\n| filelock | `FileLock(p, timeout=5).timeout` | second `FileLo... | 2026-09-17 20:04:06 | 2026-09-24 07:24:10 | null | null | CONTRIBUTOR | [] | null | null | null | null | ### Describe the bug
`datasets.utils._filelock.FileLock` silently discards every keyword argument except `lock_file`. Passing `timeout=` has no effect, and `is_singleton=True` raises instead of returning the cached lock.
The wrapper declares a variadic signature:
```python
# src/datasets/utils/_filelock.py
def __ini... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8617 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8617/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8617/comments | https://api.github.com/repos/huggingface/datasets/issues/8617/events | https://github.com/huggingface/datasets/issues/8617 | 5,448,559,498 | I_kwDODunzps8AAAABRMJrig | 8,617 | `SplitDict.copy()` crashes when `dataset_name` is not set | {
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"I'd like to take this one.\n\nReproduced on datasets 5.0.1 with the snippet above. `SplitDict.from_split_dict()` reads `dataset_name` via `split_infos[0].get(...)`, which assumes a raw dict, while the loop just below it already handles both dicts and `SplitInfo` objects. I'll branch the lookup the same way and cov... | 2026-09-14 11:12:15 | 2026-09-24 09:07:48 | null | null | NONE | [] | null | null | null | null | ## Description
`SplitDict.copy()` (and `SplitDict.from_split_dict`) crashes with
`AttributeError: 'SplitInfo' object has no attribute 'get'` whenever the split
dict contains `SplitInfo` objects and `dataset_name` is `None`.
## Reproduction
```python
from datasets import SplitDict, SplitInfo
split_dict = SplitDict({... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8714 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8714/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8714/comments | https://api.github.com/repos/huggingface/datasets/issues/8714/events | https://github.com/huggingface/datasets/issues/8714 | 5,647,821,325 | I_kwDODunzps8AAAABUKLqDQ | 8,714 | Casting mixed JSON and plain strings to Json depends on row order and batch size | {
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"#self-assign\n\nI have reproduced this on current main and prepared a focused fix using the existing per-value encoding rule, with regression tests for both row orders and multiple batch sizes."
] | 2026-09-30 14:11:42 | 2026-09-30 14:12:11 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
Casting a string column containing both JSON-encoded values and plain strings to `Json()` gives different results depending on row order and `batch_size`. A plain string among the first five rows makes valid JSON values decode as strings; a plain string after those rows is left unencoded and raise... | null | {
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"html_url": "https://github.com/charan-rathore",
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"#self-assign"
] | 2026-09-29 08:17:13 | 2026-09-29 08:19:03 | null | {
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`string_to_dict` creates named groups for format fields, but builds the result by zipping field names with every regex capture. An unrelated capturing group shifts the values.
## Reproduction
```python
from datasets.utils.py_utils import string_to_dict
print(string_to_dict("train/alice", "(train|test)/{na... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8675 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8675/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8675/comments | https://api.github.com/repos/huggingface/datasets/issues/8675/events | https://github.com/huggingface/datasets/issues/8675 | 5,560,824,749 | I_kwDODunzps8AAAABS3NzrQ | 8,675 | load_dataset("json") fails on mixed-shape JSONL when a chunksize boundary separates the shapes | {
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"Hi, I'd like to work on this issue.\n\nI'll first reproduce the failure with a focused test, then investigate how schemas are inferred and aligned across JSONL chunks in `Json._generate_tables`.\n\nMy initial approach is to make chunked loading consistent with single-chunk loading by unifying the columns and filli... | 2026-09-23 23:31:51 | 2026-09-24 00:46:12 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
`load_dataset("json")` raises `DatasetGenerationError` ("column names don't match") on a valid JSONL file that mixes two record shapes, whenever the default 10MB `chunksize` splits the file so that different chunks see different sets of columns.
The JSON loader reads the file in `chunksize` batch... | null | {
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`datasets.utils._filelock.FileLock` silently discards every keyword argument except `lock_file`. Passing `timeout=` has no effect, and `is_singleton=True` raises instead of returning the cached lock.
The wrapper declares a variadic signature:
```python
# src/datasets/utils/_filelock.py
def __ini... | null | {
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`SplitDict.copy()` (and `SplitDict.from_split_dict`) crashes with
`AttributeError: 'SplitInfo' object has no attribute 'get'` whenever the split
dict contains `SplitInfo` objects and `dataset_name` is `None`.
## Reproduction
```python
from datasets import SplitDict, SplitInfo
split_dict = SplitDict({... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8596 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8596/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8596/comments | https://api.github.com/repos/huggingface/datasets/issues/8596/events | https://github.com/huggingface/datasets/issues/8596 | 5,413,314,229 | I_kwDODunzps8AAAABQqietQ | 8,596 | load_dataset silently accepts out-of-range ClassLabel indices when the source dtype already matches | {
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"Hi! I’d like to work on this issue.\n\nI can reproduce the inconsistent behavior between `from_dict()` and `from_json()` / `from_parquet()`, and I’d like to add regression coverage for out-of-range `ClassLabel` indices while keeping the existing fast path intact where possible.\n\nWould you be okay with me working... | 2026-09-10 14:15:14 | 2026-09-16 08:05:39 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
Loading a file whose parsed Arrow dtype already matches a declared `ClassLabel`'s storage type (`int64`) skips the range check entirely. Out-of-range indices load with no error and no warning, and only surface later at `int2str` time or as silently wrong labels during training.
```python
from dat... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8590 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8590/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8590/comments | https://api.github.com/repos/huggingface/datasets/issues/8590/events | https://github.com/huggingface/datasets/issues/8590 | 5,391,094,167 | I_kwDODunzps8AAAABQVWRlw | 8,590 | record_checksums default changed True -> False in 4.8.5, not in the release notes | {
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"I'm adding it to the release notes, thx !",
"Looks like the default for `record_checksums` was switched from True to False in 4.8.5, but it wasn't mentioned in the release notes. This could impact users relying on checksums for data verification.\n"
] | 2026-09-08 19:36:25 | 2026-09-16 23:00:38 | null | null | NONE | [] | null | null | null | null | ### What changed
Between 4.8.4 and 4.8.5, checksum recording flipped from on to off by default in two places. From the sdists:
```
4.8.4 src/datasets/download/download_manager.py:80 record_checksums=True
4.8.5 src/datasets/download/download_manager.py:80 record_checksums=False
4.8.4 src/datasets/utils/info_ut... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8543 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8543/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8543/comments | https://api.github.com/repos/huggingface/datasets/issues/8543/events | https://github.com/huggingface/datasets/issues/8543 | 5,308,784,806 | I_kwDODunzps8AAAABPG2gpg | 8,543 | xPath.glob passes double-wrapped storage options to url_to_fs | {
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"#self-assign\n",
"#self-assign"
] | 2026-09-01 06:58:36 | 2026-09-01 08:48:03 | null | null | CONTRIBUTOR | [] | null | null | null | null | ### Describe the bug
`xPath.glob` adds a second protocol key to the storage options before passing them to `url_to_fs`, so fsspec receives `https={'https': {...}}` instead of `https={...}`.
`_prepare_path_and_storage_options` already returns them protocol keyed, and the docstring of `_prepare_single_hop_path_and_stor... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8537 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8537/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8537/comments | https://api.github.com/repos/huggingface/datasets/issues/8537/events | https://github.com/huggingface/datasets/issues/8537 | 5,291,992,964 | I_kwDODunzps8AAAABO21nhA | 8,537 | JPEG XL support | {
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"I think we just need to make sure Pillow can load such images, and if we need a plugin of some sort or no.\n\nIn the Viewer images will appear on browsers that support JXL",
"For Pillow you have e.g. https://pypi.org/project/pillow-jxl-plugin/\n\nFor the Dataset Viewer and the Data Studio I don't see any images,... | 2026-08-30 12:13:56 | 2026-09-02 18:34:32 | null | null | NONE | [] | null | null | null | null | It seems that the dataset don't support JXL natively in the same ways as e.g. PNG and JPEG are supported. A JPEG XL is supported by an international ISO standard, gives great compression ratios, finally supports lossless for JPEG and the browser support is now starting to get wide spread (safari has it for some time ->... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8522 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8522/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8522/comments | https://api.github.com/repos/huggingface/datasets/issues/8522/events | https://github.com/huggingface/datasets/issues/8522 | 5,277,366,650 | I_kwDODunzps8AAAABOo45eg | 8,522 | Docs proposal: relabel left/right segmentation classes during horizontal flips | {
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"Hi! Opening a PR for this docs request.\n\nAdded a section that flips image/mask together and swaps the directional label pairs on the human parsing dataset, plus an optional AlbumentationsX mapping for folks who already use that stack.\n\n#self-assign"
] | 2026-08-28 10:39:42 | 2026-09-02 03:48:31 | null | null | CONTRIBUTOR | [] | null | null | null | null | ### Feature request
Would you be open to a self-contained documentation recipe showing how to relabel directional semantic classes during a horizontal flip? It could be a separate section in [`docs/source/semantic_segmentation.mdx`](https://github.com/huggingface/datasets/blob/main/docs/source/semantic_segmentation.md... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8507 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8507/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8507/comments | https://api.github.com/repos/huggingface/datasets/issues/8507/events | https://github.com/huggingface/datasets/issues/8507 | 5,228,485,367 | I_kwDODunzps8AAAABN6Ra9w | 8,507 | ArrayXD silently reshapes inputs with incompatible nested dimensions | {
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"#self-assign"
] | 2026-08-23 18:42:56 | 2026-08-23 18:43:58 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
`Array2D` and the other `ArrayXD` features accept nested input whose dimensions do not match the declared shape when the total number of values happens to match.
For example, data shaped like `(2, 2)` can be created from rows of lengths `3` and `1`. When the value is read back, the rows are silen... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8499 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8499/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8499/comments | https://api.github.com/repos/huggingface/datasets/issues/8499/events | https://github.com/huggingface/datasets/issues/8499 | 5,192,173,564 | I_kwDODunzps8AAAABNXpH_A | 8,499 | TsFile format filter uses an inconsistent URL and is not available initially | {
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"# `tsfile` facet — neither URL names a format\n\nFindings only; no request for action. Figures carry their date. Retracted claims are kept.\n\n`?format=tsfile` and `?format=format:tsfile` are not two spellings of the same filter. They are not two routes to a `format:` facet either: `tsfile` is not in the Hub forma... | 2026-08-19 11:35:39 | 2026-09-01 04:16:37 | null | null | NONE | [] | null | null | null | null |
## Summary
There appear to be two related issues with the `TsFile` format filter on the Hugging Face Datasets page:
1. The URL parameter for `TsFile` is inconsistent with other formats.
2. `TsFile` is not initially shown in the format filter and only appears after visiting a TsFile-specific URL.
## 1. Inconsistent... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8491 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8491/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8491/comments | https://api.github.com/repos/huggingface/datasets/issues/8491/events | https://github.com/huggingface/datasets/issues/8491 | 5,168,815,070 | I_kwDODunzps8AAAABNBXb3g | 8,491 | `Dataset.map(num_proc=N)` worker crashes with `ValueError: I/O operation on closed file` when `finalize()` is interrupted | {
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"Reference: \n\n1. https://github.com/boostorg/beast/issues/1445\n2. `man 2 close`:\n```\n Dealing with error returns from close()\n A careful programmer will check the return value of close(), since it is quite possible that errors on a previous write(2) operation are reported only on the final close() that re... | 2026-08-17 06:05:58 | 2026-09-29 22:49:46 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
We hit this while running Megatron-LM training through ms-swift, which uses `datasets` under the hood for preprocessing. Our preprocessing step calls `Dataset.map()` with a fairly aggressive `num_proc=512` on a ~25k-example JSONL file:
```bash
swift --dataset_num_proc 512 --dataset large.jsonl --... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8483 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8483/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8483/comments | https://api.github.com/repos/huggingface/datasets/issues/8483/events | https://github.com/huggingface/datasets/issues/8483 | 5,160,294,983 | I_kwDODunzps8AAAABM5PaRw | 8,483 | Dataset.take(n) raises IndexError when n > len(dataset), but IterableDataset.take(n) returns what it has | {
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"I'll work on this. Could you assign it to me?\n\nI'll reproduce from the report, fix the failure path, and add a test so it stays fixed.\n",
"Just checking in. I've started working on reproducing the issue and will proceed with the fix as discussed. Let me know if there are any changes in direction or additional... | 2026-08-15 16:32:03 | 2026-09-08 10:02:39 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
`Dataset.take(n)` raises when asked for more elements than the dataset has, while `IterableDataset.take(n)` returns the elements it has. Both are documented identically as "Create a new [...] with only the first `n` elements".
```python
>>> from datasets import Dataset
>>> ds = Dataset.from_dict(... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8481 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8481/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8481/comments | https://api.github.com/repos/huggingface/datasets/issues/8481/events | https://github.com/huggingface/datasets/issues/8481 | 5,158,540,024 | I_kwDODunzps8AAAABM3kS-A | 8,481 | ClassLabel.str2int and int2str do not validate the elements of an iterable | {
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"Thanks for weighing in, but one correction so the report stays accurate: `int2str` does **not** return `None` for an unknown class id. It raises, both for a bare value and inside a list — that path is already covered by the `0 <= v < num_classes` check:\n\n```python\n>>> cl = ClassLabel(names=[\"neg\", \"pos\"])\n... | 2026-08-15 08:43:11 | 2026-08-17 06:13:32 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
`ClassLabel.str2int` and `ClassLabel.int2str` both validate the *container* they're given, but never the elements inside it. Two of the resulting cases fail silently and return wrong labels rather than raising.
`str2int` accepts ints and hands them straight back, so a column of integer labels rou... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8472 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8472/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8472/comments | https://api.github.com/repos/huggingface/datasets/issues/8472/events | https://github.com/huggingface/datasets/issues/8472 | 5,128,543,479 | I_kwDODunzps8AAAABMa9c9w | 8,472 | batch(0) silently returns one batch with the whole dataset instead of raising | {
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"Hi @shashvat-singham i did also try and reproduced it and got the same results described :\n\n```text\nIterableDataset.batch(0/-1) → [5]\nDataset.batch(0/-1) → 1 batch\nbatch(2) → [2, 2, 1] / 3 batches\n```\n\nI’d like to give this a try\n\nThanks\n\n#self-assign"
] | 2026-08-12 07:52:28 | 2026-08-16 15:56:35 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
`Dataset.batch()` and `IterableDataset.batch()` accept `batch_size=0` and negative sizes, and quietly return **one batch holding the whole dataset**. Asking for a zero-sized batch produces the largest possible batch, which is as close to the opposite of the request as the API can get.
### Steps o... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8458 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8458/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8458/comments | https://api.github.com/repos/huggingface/datasets/issues/8458/events | https://github.com/huggingface/datasets/issues/8458 | 5,110,353,136 | I_kwDODunzps8AAAABMJnM8A | 8,458 | Replace httpx with httpx2 | {
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"Hi @lhoestq can I work on this",
"I think if we would have to discuss in a https://github.com/huggingface/huggingface_hub/ issue about it and `datasets` could align with what's decided there"
] | 2026-08-10 13:01:44 | 2026-08-16 15:56:33 | null | null | NONE | [] | null | null | null | null | ### Feature request
Replace the httpx library with the [httpx2](https://github.com/pydantic/httpx2) fork, maintained by Pydantic.
### Motivation
Httpx has not been released since December 2024, and has closed all public access to Issues / Discussions / PRs, this raises questions about the actual state of maintenance... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8391 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8391/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8391/comments | https://api.github.com/repos/huggingface/datasets/issues/8391/events | https://github.com/huggingface/datasets/issues/8391 | 5,057,110,196 | I_kwDODunzps8AAAABLW1gtA | 8,391 | Nanosecond timestamps are silently truncated even when Value("timestamp[ns]") is requested | {
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"#self-assign"
] | 2026-08-04 05:36:19 | 2026-08-06 02:08:27 | null | null | CONTRIBUTOR | [] | null | null | null | null | ### Describe the bug
`Dataset.from_dict` / `from_list` / `map` silently drop sub-microsecond precision, even when the user explicitly declares a nanosecond feature type. The resulting dataset reports `timestamp[ns]` but the data has already been truncated to microseconds.
### Steps to reproduce the bug
```python
imp... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8390 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8390/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8390/comments | https://api.github.com/repos/huggingface/datasets/issues/8390/events | https://github.com/huggingface/datasets/issues/8390 | 5,057,108,509 | I_kwDODunzps8AAAABLW1aHQ | 8,390 | to_json cannot round-trip temporal columns: all timestamps written as epoch milliseconds | {
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"#self-assign\n\nOpened a fix in #8459."
] | 2026-08-04 05:36:00 | 2026-08-10 23:10:37 | null | null | CONTRIBUTOR | [] | null | null | null | null | ### Describe the bug
`Dataset.to_json()` serializes every temporal column as a bare epoch integer at a single fixed resolution (pandas' `date_unit="ms"` default), with no unit recorded in the output. Timestamps therefore do not survive a `to_json` → `from_json` round trip: they either come back silently wrong or raise... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8386 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8386/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8386/comments | https://api.github.com/repos/huggingface/datasets/issues/8386/events | https://github.com/huggingface/datasets/issues/8386 | 5,056,333,190 | I_kwDODunzps8AAAABLWGFhg | 8,386 | map(batched=True, drop_last_batch=True) returns the input unchanged when the dataset is smaller than batch_size | {
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"Confirmed on current `main` (`3e2c1a6c3`), and the `Dataset.batch()` half is worse than the title suggests: it hands back the **unbatched** input, so both the row count and the schema are wrong while `IterableDataset.batch()` correctly yields nothing.\n\nExecuted against `3e2c1a6c3` (3-row dataset, `batch_size=5`,... | 2026-08-04 03:21:59 | 2026-09-18 16:59:48 | null | null | CONTRIBUTOR | [] | null | null | null | null | ### Describe the bug
When `drop_last_batch=True` and the dataset is smaller than `batch_size`, `Dataset.map(batched=True, ...)` returns the **input unchanged** instead of an empty dataset. The mapped function is never called, but the original rows are passed through with the original (unbatched) schema.
The iterable ... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8381 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8381/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8381/comments | https://api.github.com/repos/huggingface/datasets/issues/8381/events | https://github.com/huggingface/datasets/issues/8381 | 5,053,065,106 | I_kwDODunzps8AAAABLS-nkg | 8,381 | IterableDataset.to_dict() and to_polars() return an empty generator instead of the data | {
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"#take",
"@ebarkhordar i checked #8381 on current main and both default exports still return generators. i saw you kept the branch for #8382. are you planning to reopen it? lmk if i can help refresh the tests, or pick it up if you've moved on.\n",
"Take it. I closed #8382 because it sat a month without a review... | 2026-08-03 18:35:13 | 2026-09-15 06:18:13 | null | null | CONTRIBUTOR | [] | null | null | null | null | ### Describe the bug
`IterableDataset.to_dict()` and `IterableDataset.to_polars()` each have a bare `yield` in their `batched=True` branch, which makes the whole method a generator function. Calling either one the way its docstring shows returns a generator that yields nothing, and the value the `else` branch returns ... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8375 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8375/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8375/comments | https://api.github.com/repos/huggingface/datasets/issues/8375/events | https://github.com/huggingface/datasets/issues/8375 | 5,025,604,085 | I_kwDODunzps8AAAABK4yh9Q | 8,375 | `PandasArrayExtensionDtype._metadata` should be a tuple, not a string | {
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"#self-assign"
] | 2026-07-31 01:50:02 | 2026-08-12 06:30:29 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
There's a small typo in `PandasArrayExtensionDtype` (`src/datasets/features/features.py`):
```python
_metadata = "value_type"
```
Pandas expects `_metadata` to be a tuple of attribute names, like `("value_type",)`, not a plain string ([API documentation ref](https://pandas.pydata.org/docs/refer... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8373 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8373/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8373/comments | https://api.github.com/repos/huggingface/datasets/issues/8373/events | https://github.com/huggingface/datasets/issues/8373 | 5,010,686,962 | I_kwDODunzps8AAAABKqkD8g | 8,373 | TypeError in _dill.py _batch_setitems with Python 3.14 | {
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"Hey Mates, this works: In src/datasets/utils/_dill.py, starting around line 71, update the _batch_setitems overriding to pass the obj argument downstream.\n\n def _batch_setitems(self, items, obj=None):\n if self._legacy_no_dict_keys_sorting:\n return super()._batch_setitems(items,... | 2026-07-29 15:00:19 | 2026-08-29 21:30:28 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
When using `load_dataset` on Python 3.14, a `TypeError` is raised during the fingerprinting process inside the bundled `_dill.py`. This happens because Python 3.14 changed the signature of the internal C-level `_Pickler._batch_setitems` to require 3 arguments (`self, items, obj`), while `datasets/... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8359 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8359/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8359/comments | https://api.github.com/repos/huggingface/datasets/issues/8359/events | https://github.com/huggingface/datasets/issues/8359 | 4,964,932,317 | I_kwDODunzps8AAAABJ-7a3Q | 8,359 | IterableDataset.filter() checkpoint/resume silently drops the rest of the in-flight Arrow table | {
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"#self-assign"
] | 2026-07-24 03:36:32 | 2026-07-24 12:06:21 | 2026-07-24 12:06:21 | null | CONTRIBUTOR | [] | null | null | null | null | ### Describe the bug
Resuming a streaming `IterableDataset.filter()` from a `state_dict()` checkpoint silently drops rows: the remainder of the in-flight Arrow table is skipped. For a single-shard dataset this loses up to a full row group per checkpoint, and for a single-table shard it can drop every unconsumed row.
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https://api.github.com/repos/huggingface/datasets/issues/8341 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8341/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8341/comments | https://api.github.com/repos/huggingface/datasets/issues/8341/events | https://github.com/huggingface/datasets/issues/8341 | 4,917,723,283 | I_kwDODunzps8AAAABJR6Akw | 8,341 | concatenate_datasets(axis=1) with Arrow format drops the first source's columns | {
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"#self-assign"
] | 2026-07-18 09:41:43 | 2026-07-22 18:35:31 | 2026-07-22 18:35:31 | null | CONTRIBUTOR | [] | null | null | null | null | ### Describe the bug
The Arrow fast path of horizontal concatenation (`concatenate_datasets([...], axis=1)` consumed through `.with_format("arrow")`, or any Arrow/tensor consumer) drops the columns of the first source. The plain-Python path is correct; only the Arrow path diverges.
`HorizontallyConcatenatedMultiSourc... | {
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https://api.github.com/repos/huggingface/datasets/issues/8331 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8331/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8331/comments | https://api.github.com/repos/huggingface/datasets/issues/8331/events | https://github.com/huggingface/datasets/issues/8331 | 4,883,801,676 | I_kwDODunzps8AAAABIxjmTA | 8,331 | datasets-server.huggingface.co returning 503 on every endpoint (whole host down, not one route) | {
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"Hi ! Thanks for the ping, yes we are aware of the issue and actively working on it. It's taking some time though since we want to make sure it will be 100% back and for good.\n\nThis impacts both the API and the Viewer on HF which is based on it",
"Seems to be up and running properly now I'll conclude this issue... | 2026-07-14 13:59:29 | 2026-07-17 12:09:35 | 2026-07-17 12:09:34 | null | NONE | [] | null | null | null | null | ### Describe the bug
The entire datasets-server.huggingface.co backend (the dataset-viewer API) is
returning 503 Service Temporarily Unavailable on every route I've tried, not
just one endpoint. It reproduces on public datasets with no auth token, so it
doesn't appear to be account- or dataset-specific. huggingface.co... | {
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https://api.github.com/repos/huggingface/datasets/issues/8330 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8330/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8330/comments | https://api.github.com/repos/huggingface/datasets/issues/8330/events | https://github.com/huggingface/datasets/issues/8330 | 4,883,330,907 | I_kwDODunzps8AAAABIxG3Ww | 8,330 | Dataset Studio and Viewer down | {
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"Hi ! Thanks for the ping, yes we are aware of the issue and actively working on it. It's taking some time though since we want to make sure it will be 100% back and for good"
] | 2026-07-14 13:06:53 | 2026-07-24 15:26:15 | 2026-07-24 15:26:15 | null | NONE | [] | null | null | null | null | ### Describe the bug
Hello!
I want to report a bug on the datasets viewer and data studio pages. I have attempted to access it on various datasets from various devices and it will not let me view the dataset this way. I have tried restarting, login in and out but to no success. I use Hugging Face as a repository th... | {
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https://api.github.com/repos/huggingface/datasets/issues/8328 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8328/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8328/comments | https://api.github.com/repos/huggingface/datasets/issues/8328/events | https://github.com/huggingface/datasets/issues/8328 | 4,881,665,580 | I_kwDODunzps8AAAABIvhOLA | 8,328 | Streaming datasets fail with 403 SignatureError: invalid key pair id from xet-bridge-us (Colab, latest libraries) | {
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"Hi ! I couldn't reproduce the issue on my side. I can see two options, let me know if any helps you:\n\n1) this was a transient issue (we restarted some machines recently but this shouldn't have impacted you tbh), can you try again just in case ?\n2) something is wrong with your token smh, can you logout and login... | 2026-07-14 09:21:43 | 2026-07-24 15:26:24 | 2026-07-24 15:26:24 | null | NONE | [] | null | null | null | null | ### Describe the bug
I'm unable to stream datasets from the Hugging Face Hub. The issue affects both public datasets (e.g. beans) and gated datasets (ILSVRC/imagenet-1k).
The failure occurs before any examples are yielded. The request is redirected to the Xet CDN (xet-bridge-us) and fails with:
```
403 Forbidden
Au... | {
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https://api.github.com/repos/huggingface/datasets/issues/8327 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8327/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8327/comments | https://api.github.com/repos/huggingface/datasets/issues/8327/events | https://github.com/huggingface/datasets/issues/8327 | 4,874,477,254 | I_kwDODunzps8AAAABIoqexg | 8,327 | `Dataset.from_pandas` allocates ~1 MB per Arrow chunk, Out of Memory errors | {
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"The measurements in the issue point at `from_pandas`, but I think the allocation is actually in fingerprinting, and not in the Arrow conversion at all.\n\nOn datasets 5.0.0 I get:\n\n| step | peak |\n|---|---|\n| `pa.Table.from_pandas(df)` | ~0 MB |\n| `Dataset.from_pandas(df)` | 1499 MB |\n| `generate_fingerprint... | 2026-07-13 14:13:38 | 2026-07-22 17:28:51 | 2026-07-22 17:28:51 | null | NONE | [] | null | null | null | null | ### Describe the bug
`Dataset.from_pandas` memory usage scales with the chunk count of the backing Arrow array (around 1 MB per chunk).
`Dataset.shuffle()` followed by `to_pandas()` produces string columns with one chunk per row, so a 25k-row DataFrame holding ~32 MB of text allocates ~30 GB on the way back through ... | {
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https://api.github.com/repos/huggingface/datasets/issues/8324 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8324/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8324/comments | https://api.github.com/repos/huggingface/datasets/issues/8324/events | https://github.com/huggingface/datasets/issues/8324 | 4,867,649,641 | I_kwDODunzps8AAAABIiJwaQ | 8,324 | Path traversal / arbitrary file read via the `file_name` metadata field in `*folder` dataset builders (no `trust_remote_code`) | {
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"#self-assign"
] | 2026-07-12 15:38:21 | 2026-07-23 15:37:57 | 2026-07-23 15:37:57 | null | NONE | [] | null | null | null | null | ### Describe the bug
reported via email on 9 June 2026 - no acknowledgement or response:
Package: datasets (PyPI). Affected file: src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py
Affected Versions: confirmed on 5.0.0 (PyPI) and HEAD 63e103e.
CVSS: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N... | {
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https://api.github.com/repos/huggingface/datasets/issues/8308 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8308/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8308/comments | https://api.github.com/repos/huggingface/datasets/issues/8308/events | https://github.com/huggingface/datasets/issues/8308 | 4,818,109,751 | I_kwDODunzps8AAAABHy6FNw | 8,308 | Streaming IterableDataset state stops advancing after first resume — second resume restarts from the beginning | {
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"@francesco-bertolotti Hi maintainers! I am an NLP intern at Sunbird AI and a first-time contributor. I would love to work on this issue. Could you please assign it to me?",
"Thank you for your interest @SsemuliJoseph \n\nThe fix was merged 2 weeks ago https://github.com/huggingface/datasets/pull/8295\nI should p... | 2026-07-06 10:12:27 | 2026-07-24 07:58:49 | 2026-07-23 13:12:33 | null | CONTRIBUTOR | [] | null | null | null | null |
## Description
For a streaming `IterableDataset`, calling `load_state_dict()` and then continuing to iterate leaves `state_dict()` frozen at the initial position (`shard_idx=0`, `shard_example_idx=0`). Reading resumes correctly the first time, but the tracked state never advances again.
This causes a second consecut... | {
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https://api.github.com/repos/huggingface/datasets/issues/8302 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8302/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8302/comments | https://api.github.com/repos/huggingface/datasets/issues/8302/events | https://github.com/huggingface/datasets/issues/8302 | 4,804,667,688 | I_kwDODunzps8AAAABHmFpKA | 8,302 | Turkish DIK-style Syntactic Structure Benchmark Dataset | {
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"Hi! I'd be interested in helping with this benchmark. I have experience working with NLP datasets and Hugging Face tooling, and I'd be happy to contribute on the engineering side (dataset packaging, loading script, validation, documentation, evaluation utilities, or testing). If you're planning to move forward, I'... | 2026-07-03 15:33:39 | 2026-08-27 07:40:40 | null | null | NONE | [] | null | null | null | null | ### Feature request
A structured dataset proposal introducing a Turkish syntactic structure benchmark designed for evaluating LLMs on fine-grained grammatical reasoning in a morphologically rich language.
Current NLP datasets in Hugging Face focus heavily on surface-level semantic tasks or English-centric benchmarks.... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8296 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8296/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8296/comments | https://api.github.com/repos/huggingface/datasets/issues/8296/events | https://github.com/huggingface/datasets/issues/8296 | 4,779,554,534 | I_kwDODunzps8AAAABHOI25g | 8,296 | [security] Symlink-Following Arbitrary File Write via Archive Extraction in huggingface/datasets | {
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"thanks for reporting, I'm not entirely sure how someone could exploit this but a fix would be welcome for sure ! Option A looks good to me",
"@lhoestq Thanks for the quick response! I opened a PR #8303 implementing Option A. The threat model is a shared cache. Any user who can write into downloads/extracted/ — b... | 2026-06-30 18:46:34 | 2026-08-29 21:30:27 | null | null | CONTRIBUTOR | [] | null | null | null | null | ### Describe the bug
## Summary
A symlink-following vulnerability exists in the archive extraction subsystem of `huggingface/datasets` that allows a local attacker with write access to a shared HuggingFace cache directory to write arbitrary files with the victim's privileges, by pre-planting a symlink at a predictabl... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8293 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8293/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8293/comments | https://api.github.com/repos/huggingface/datasets/issues/8293/events | https://github.com/huggingface/datasets/issues/8293 | 4,774,067,106 | I_kwDODunzps8AAAABHI57og | 8,293 | Support concatenating multiple streaming datasets while preserving the sum of shards | {
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"it's already the case afaik:\n\n```python\nIn [1]: from datasets import IterableDataset, concatenate_datasets\n\nIn [2]: ds1 = IterableDataset.from_dict({\"i\": [0, 1]})\n\nIn [3]: ds2 = IterableDataset.from_dict({\"i\": [2, 3]})\n\nIn [4]: ds = concatenate_datasets([ds1, ds2])\n\nIn [5]: list(ds)\nOut[5]: [{'i': ... | 2026-06-30 05:44:23 | 2026-07-03 13:40:43 | null | null | NONE | [] | null | null | null | null | ### Feature request
It would be useful if concatenating multiple `IterableDataset`s could preserve the shard information from each input dataset, so that:
- the total number of shards equals the sum of the input shards;
- `split_dataset_by_node()` and worker sharding continue to work efficiently;
- downstream distrib... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8256 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8256/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8256/comments | https://api.github.com/repos/huggingface/datasets/issues/8256/events | https://github.com/huggingface/datasets/issues/8256 | 4,627,616,612 | I_kwDODunzps8AAAABE9PTZA | 8,256 | Dataset Viewer fails on TSFile datasets | {
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"Thanks for reporting ! I'm working on it :)\n\nThe viewer doesn't use `datasets` V5 yet, I have to do some minor adjustments first",
"I opened a PR that addresses the missing optional tsfile dependency error by replacing the raw ModuleNotFoundError with a clearer ImportError and adding a regression test.\n\nThis... | 2026-06-10 03:15:32 | 2026-07-06 01:52:51 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
## Description
The Dataset Viewer fails when trying to display a dataset stored in TSFile format.
The error shown by the viewer is:
```python
ModuleNotFoundError: No module named 'tsfile'
### Steps to reproduce the bug
# Dataset Viewer fails to load TSFile dataset due to missing `tsfile` depe... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8253 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8253/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8253/comments | https://api.github.com/repos/huggingface/datasets/issues/8253/events | https://github.com/huggingface/datasets/issues/8253 | 4,618,455,811 | I_kwDODunzps8AAAABE0gLAw | 8,253 | Feature request: Add a streaming_shard operator for early sample-level sharding when file-level sharding is insufficient | {
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"I feel like IterableDatasetShard is not well suited for this and shouldn't be used / should be improved. Instead there is `ds.shard()` or even `split_dataset_by_node()` which works when `num_physical_files < global_world_size`. WDYT ?",
"I checked current `main`, and the requested behavior seems to sit between t... | 2026-06-09 03:14:46 | 2026-09-09 13:54:29 | 2026-09-09 13:54:29 | null | NONE | [] | null | null | null | null | ## Feature request: Add a streaming_shard operator for early sample-level sharding when file-level sharding is insufficient
### Proposed API
It would be useful to provide a first-class streaming sharding operator in `datasets`, for example:
```python
dataset = datasets.load_dataset(..., streaming=True, split="train"... | {
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https://api.github.com/repos/huggingface/datasets/issues/8246 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8246/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8246/comments | https://api.github.com/repos/huggingface/datasets/issues/8246/events | https://github.com/huggingface/datasets/issues/8246 | 4,606,509,015 | I_kwDODunzps8AAAABEpG_1w | 8,246 | RecursionError when loading GLB file with deeply nested JSON in Mesh feature | {
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"#self-assign"
] | 2026-06-07 07:10:22 | 2026-08-12 06:46:48 | null | null | NONE | [] | null | null | null | null | ## Description
Loading a GLB file with deeply nested JSON chunk causes a RecursionError, crashing the application.
## Step to Reproduce
```python
from datasets import Dataset, Mesh
import tempfile, os, struct
def make_malicious_glb(depth=5000):
json_chunk = (b'{"a":' * depth + b'1' + b'}' * depth)
magic = b... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8242 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8242/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8242/comments | https://api.github.com/repos/huggingface/datasets/issues/8242/events | https://github.com/huggingface/datasets/issues/8242 | 4,599,059,760 | I_kwDODunzps8AAAABEiAVMA | 8,242 | "eval_strategy": "no" perform evaluation | {
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"Wrong repo, this belongs in axolotl, not `datasets`. And `eval_strategy: \"no\"` was never going to stop it.\n\nWhat hangs you is the diffusion plugin's sample generation. `DiffusionGenerationCallback.on_step_end` fires on `global_step % generation_interval == 0` and ignores `eval_strategy`. When you have no eval ... | 2026-06-05 18:08:17 | 2026-06-20 14:48:43 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
Hi,
I'm trying to train a diffusion model and I getting stuck with
```
strace -p 967873
strace: Process 967873 attached
ioctl(9, _IOC(_IOC_READ|_IOC_WRITE, 0x46, 0x2a, 0x20), 0x7fff18579d90) = 0
ioctl(9, _IOC(_IOC_READ|_IOC_WRITE, 0x46, 0x2a, 0x20), 0x7fff18579d90) = 0
```
But my issue is that ... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8241 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8241/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8241/comments | https://api.github.com/repos/huggingface/datasets/issues/8241/events | https://github.com/huggingface/datasets/issues/8241 | 4,597,756,669 | I_kwDODunzps8AAAABEgwy_Q | 8,241 | load_dataset("json", ...) infers a different schema when the JSONL file starts with a UTF-8 BOM | {
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"#self-assign"
] | 2026-06-05 14:39:46 | 2026-06-09 15:48:27 | 2026-06-09 15:48:27 | null | NONE | [] | null | null | null | null | ### Describe the bug
When a JSONL file starts with a UTF-8 BOM (`\xef\xbb\xbf`), `datasets.load_dataset("json", data_files=...)` infers a different schema than when the same file is loaded without the BOM. Specifically, the loader's "mixed-struct-types" pre-scan — which normally promotes columns with heterogeneous nes... | {
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https://api.github.com/repos/huggingface/datasets/issues/8217 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8217/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8217/comments | https://api.github.com/repos/huggingface/datasets/issues/8217/events | https://github.com/huggingface/datasets/issues/8217 | 4,501,694,591 | I_kwDODunzps8AAAABDFJofw | 8,217 | Multi-GPU Training with Large Dataset — NCCL Timeouts / Slow Data Loading + Excessive Memory Usage with keep_in_memory=True | {
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"Hi @D222097,\n\nWe have audited the architectural footprint of your multi-GPU training setup. The behaviors you are experiencing are not bugs within the `datasets` library, but rather fundamental limitations of Python's process architecture interacting with hardware topologies. \n\nHere is the clinical breakdown o... | 2026-05-22 09:55:13 | 2026-06-03 02:12:43 | 2026-06-03 02:12:43 | null | NONE | [] | null | null | null | null | Hi, I'm training a large dataset using Lerobot (which relies on Hugging Face Datasets) and encountering severe performance issues when scaling to multi-GPU training.
### Problem Description
- Unstable/slow data loading + NCCL timeouts
- Step time fluctuates drastically: ~1s/step (fast) vs ~45s/step (extremely slow)
... | {
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https://api.github.com/repos/huggingface/datasets/issues/8201 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8201/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8201/comments | https://api.github.com/repos/huggingface/datasets/issues/8201/events | https://github.com/huggingface/datasets/issues/8201 | 4,456,407,352 | I_kwDODunzps8AAAABCZ9hOA | 8,201 | Encountered an error when loading data in WebDataset format using `load_datasets` during multi-matchines training. | {
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"Hi @aihao2000 ! I was looking into this multi-machine training scenario and just opened a PR (#8203 ) that safely skips feature inference for empty shards during distributed streaming.\n\nplease! Check it out and see if it looks like it will resolve the weird bugs you were hitting!",
"it looks like there less da... | 2026-05-15 19:21:24 | 2026-05-20 12:58:57 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
Single-machine training works fine, but multi-machine training throws up all sorts of weird bugs. Help me!
### Steps to reproduce the bug
train_dataset = load_dataset(
"webdataset", data_files=args.train_dataset, split="train", streaming=True,cache_dir='/dev/shm/.cache'
)
args.train... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8199 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8199/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8199/comments | https://api.github.com/repos/huggingface/datasets/issues/8199/events | https://github.com/huggingface/datasets/issues/8199 | 4,455,786,605 | I_kwDODunzps8AAAABCZXobQ | 8,199 | Replace AutoFeatureExtractor with AutoImageProcessor in image preprocessing docs | {
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"I'd like to work on this. I'll open a PR shortly."
] | 2026-05-15 17:34:53 | 2026-07-22 17:35:56 | 2026-07-22 17:35:56 | null | NONE | [] | null | null | null | null | ## Summary
The `docs/source/use_dataset.mdx` documentation uses `AutoFeatureExtractor` from `transformers` in its image preprocessing example. For vision models, `AutoImageProcessor` is now the recommended API and better reflects current `transformers` conventions.
## Problem
In the [[Apply data augmentations](https... | {
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https://api.github.com/repos/huggingface/datasets/issues/8197 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8197/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8197/comments | https://api.github.com/repos/huggingface/datasets/issues/8197/events | https://github.com/huggingface/datasets/issues/8197 | 4,452,221,355 | I_kwDODunzps8AAAABCV-Bqw | 8,197 | Feature Request / Discussion: Skip origin_metadata fetch when streaming=True? | {
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"I think it's great that it checks that every file does exist by default. It's relatively cheap since it uses fsspec which caches file info at folder level.\n\nOn the other hand why not add skip_origin_metadata=False from @TheDerbiedOne by default to DatasetBuilder and document what it does (load_dataset passes kwa... | 2026-05-15 07:43:57 | 2026-06-17 03:39:14 | null | null | CONTRIBUTOR | [] | null | null | null | null | Hi team!
I've been looking into the initialization process of the `DatasetBuilder` and noticed that the ETag/origin metadata caching path is executed unconditionally.
While fetching the `origin_metadata` and calculating the ETag is necessary for safely managing a local disk cache when using `as_dataset()`, it seems t... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8178 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8178/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8178/comments | https://api.github.com/repos/huggingface/datasets/issues/8178/events | https://github.com/huggingface/datasets/issues/8178 | 4,397,310,407 | I_kwDODunzps8AAAABBhmhxw | 8,178 | The full dataset viewer is not available (click to read why). Only showing a preview of the rows. Job manager crashed while running this job (missing heartbeats). Error code: JobManagerCrashedError | {
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"Oh yeah, we hit something pretty similar when running a dataset viewer on a large collection (~3M rows) a few months back. The JobManagerCrashedError with missing heartbeats usually showed up for us when the server process ran out of memory or couldn’t keep up with the load spikes during dataset streaming. Turns o... | 2026-05-07 08:33:48 | 2026-05-31 00:09:38 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
Job manager crashed while running this job (missing heartbeats).
Error code: JobManagerCrashedError
see: https://huggingface.co/datasets/Genius-Society/tt100k/viewer
### Steps to reproduce the bug... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8171 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8171/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8171/comments | https://api.github.com/repos/huggingface/datasets/issues/8171/events | https://github.com/huggingface/datasets/issues/8171 | 4,376,879,740 | I_kwDODunzps8AAAABBOHifA | 8,171 | Dataset UI shows 0:00/0:00 for audio after push_to_hub | {
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"Hello,\nI am trying to find my first issue to resolve. I can't reproduce your problem. When I go in the hub UI to your dataset. I can see the length of each audio. It takes some time to load \n\n## Dataset Card\n<img width=\"584\" height=\"644\" alt=\"Image\" src=\"https://github.com/user-attachments/assets/8b0e38... | 2026-05-04 13:17:25 | 2026-05-20 10:46:58 | 2026-05-20 10:46:58 | null | NONE | [] | null | null | null | null | I’m seeing an issue where audio previews in the dataset viewer show `0:00/0:00` after uploading with push_to_hub.
## What I did
I tried to avoid `torchcodec` because I want to keep the packages small using the following code:
```python
import io
import os
import shutil
import tempfile
from pathlib import Path
imp... | {
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https://api.github.com/repos/huggingface/datasets/issues/8169 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8169/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8169/comments | https://api.github.com/repos/huggingface/datasets/issues/8169/events | https://github.com/huggingface/datasets/issues/8169 | 4,366,520,018 | I_kwDODunzps8AAAABBEPO0g | 8,169 | Streaming dataset hangs consistently | {
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"+1 also encountered",
"I pushed a workaround for the current version of PyArrow (24.0.0) and older versions at https://github.com/huggingface/datasets/pull/8176\n\nFor future versions it should be fixed directly in PyArrow"
] | 2026-05-01 20:27:58 | 2026-05-06 16:07:04 | 2026-05-06 16:06:08 | null | NONE | [] | null | null | null | null | ### Describe the bug
When loading a dataset with `streaming=True`, some background process prevents the script from ever returning (or at least for a very long time).
This did not happen with `huggingface-hub < 1`.
### Steps to reproduce the bug
from datasets import load_dataset
ds = load_dataset("IRIIS-RESEARCH/N... | {
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https://api.github.com/repos/huggingface/datasets/issues/8167 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8167/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8167/comments | https://api.github.com/repos/huggingface/datasets/issues/8167/events | https://github.com/huggingface/datasets/issues/8167 | 4,356,674,999 | I_kwDODunzps8AAAABA62Vtw | 8,167 | [BUG] Abnormal progress bar in dataset.map when load_from_cache_file=False | {
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"https://github.com/huggingface/datasets/blob/4e3bf52ff436d841e61211dfa096b5c47197ae36/src/datasets/arrow_dataset.py#L3593-L3598",
"Hi, can you provide more details on the issue ?",
"<img width=\"340\" height=\"26\" alt=\"Image\" src=\"https://github.com/user-attachments/assets/0dca6f47-4a8d-4871-a908-f58df856e... | 2026-04-30 08:47:53 | 2026-05-29 10:59:07 | 2026-05-29 10:59:07 | null | NONE | [] | null | null | null | null | ### Describe the bug
datasets 4.8.5
```python
from datasets import load_dataset, load_from_disk
data = load_from_disk('pretrain_cached_dataset/train')
def dummy_map(example):
return example
dataset = data.map(dummy_map)
dataset = data.map(dummy_map, load_from_cache_file=True) ... | {
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https://api.github.com/repos/huggingface/datasets/issues/8165 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8165/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8165/comments | https://api.github.com/repos/huggingface/datasets/issues/8165/events | https://github.com/huggingface/datasets/issues/8165 | 4,354,878,889 | I_kwDODunzps8AAAABA5ItqQ | 8,165 | IterableDataset: corrupted EXIF image silently terminates streaming iterator instead of skipping the sample | {
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"Hi ! Would it be acceptable to return None instead of skipping ? This way we can provide the same API for non-streaming (since the length of the dataset is known in advance and fixed). Then a subsequent .filter call can take care of skipping the samples. Something like this maybe ?\n\n```python\nds = load_dataset(... | 2026-04-30 02:20:54 | 2026-07-13 15:57:08 | null | null | NONE | [] | null | null | null | null | ## Summary
When iterating over a streaming `IterableDataset` that contains images with corrupted EXIF metadata (e.g., a TIFF rational tag with denominator=0), PIL raises `ZeroDivisionError` inside `exif_transpose`. This exception propagates through the HuggingFace `datasets` pipeline and **terminates the streaming ite... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8164 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8164/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8164/comments | https://api.github.com/repos/huggingface/datasets/issues/8164/events | https://github.com/huggingface/datasets/issues/8164 | 4,354,825,277 | I_kwDODunzps8AAAABA5FcPQ | 8,164 | Lance: HF auth token dropped for private repos in streaming mode (broken `storage_options` lookup) | {
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"I can see the fix. Changing `split(\"://\", 0)` to `split(\"://\", 1)` and removing the `+ \"://\"` suffix. The key lookup should be `\"hf\"` not `\"hf://\"`. \nI'd like to submit a PR for this. Is this still open?",
"Well, I am already writing a PR for this, and it is just about to be submitted."
] | 2026-04-30 02:03:33 | 2026-04-30 15:38:43 | 2026-04-30 15:38:43 | null | CONTRIBUTOR | [] | null | null | null | null | ### Describe the bug
When `Lance._split_generators` receives `hf://` URIs - i.e. anywhere a `StreamingDownloadManager` is in play (`load_dataset(..., streaming=True)`, `get_dataset_split_names`, and the dataset-viewer worker) - the HF auth token is silently dropped before reaching `lance.dataset(...)`. Lance then atte... | {
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https://api.github.com/repos/huggingface/datasets/issues/8159 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8159/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8159/comments | https://api.github.com/repos/huggingface/datasets/issues/8159/events | https://github.com/huggingface/datasets/issues/8159 | 4,345,858,995 | I_kwDODunzps8AAAABAwiLsw | 8,159 | tests/conftest.py, tests/_test_patching.py, tests/fixtures/fsspec.py and other files are missing from the PYPI distribution | {
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"Hey, ran into something similar a while back when we were packaging a custom dataset loader for a client at v4.7.x. Turns out, PyPI distributions sometimes skip test files and fixtures like `conftest.py` since they're not critical for runtime—honestly, it's a packaging config thing in `setup.py` or `pyproject.toml... | 2026-04-28 20:01:05 | 2026-04-30 14:40:23 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
Version: 4.8.5
### Steps to reproduce the bug
n/a
### Expected behavior
n/a
### Environment info
n/a | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8149 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8149/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8149/comments | https://api.github.com/repos/huggingface/datasets/issues/8149/events | https://github.com/huggingface/datasets/issues/8149 | 4,316,149,021 | I_kwDODunzps8AAAABAUM1HQ | 8,149 | [Optimization] Prevent per-thread instantiation of Cloud Storage FileSystem during Data loading initialization | {
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"Is it open for contribution?",
"I think arbitrary filesystems would be recreated in every thread in any case, unlike HfFileSystem which has custom code to handle this.",
"I looked into this and I think the thread pool already shares one filesystem instance for GCS and S3, so the hoist would not change what it ... | 2026-04-23 13:09:19 | 2026-08-29 21:42:58 | null | null | NONE | [] | null | null | null | null | ### Feature request
Modify the dataset loading initialization, so that fsspec filesystem instances (like GCSFileSystem or S3FileSystem) are instantiated once in the main thread and explicitly passed down to the background threads.
By pre-instantiating the fs object in the main thread (where the directory cache from g... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8145 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8145/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8145/comments | https://api.github.com/repos/huggingface/datasets/issues/8145/events | https://github.com/huggingface/datasets/issues/8145 | 4,306,478,911 | I_kwDODunzps8AAAABAK-nPw | 8,145 | `.map()` on a streaming IterableDataset silently skips examples after load_state_dict | {
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"I think this line here is causing issues: \nhttps://github.com/huggingface/datasets/blob/2724a653e7582077be647d3fdfe8cd1fac27b85f/src/datasets/iterable_dataset.py#L2225\nIt ignored force_convert_to_python, so it consumed a full Arrow chunk.\nI think it can be fixed if you add `self.force_convert_to_python` to the ... | 2026-04-22 03:08:39 | 2026-04-27 14:03:28 | 2026-04-27 14:03:28 | null | NONE | [] | null | null | null | null | ### Describe the bug
After `ds.map(fn)` on a streaming IterableDataset, saving state_dict() and loading it into a fresh dataset does not resume at the correct position. It jumps forward by up to one Arrow read-chunk (~1000 rows).
### Steps to reproduce the bug
```python
from datasets import Dataset
ds1 = Dataset.fr... | {
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https://api.github.com/repos/huggingface/datasets/issues/8131 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8131/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8131/comments | https://api.github.com/repos/huggingface/datasets/issues/8131/events | https://github.com/huggingface/datasets/issues/8131 | 4,251,712,550 | I_kwDODunzps79a_wm | 8,131 | datasets.to_list: Behaviour change in version 4.7.0 with the addition of JSON type | {
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"I think we can go for the same approach as in https://github.com/huggingface/datasets/pull/8122 which decodes the JSON data (and supports JSON nested in other objects)\n\n(Or decide to decode all the features types, which I think could make sense, but this needs more careful handling so this should be discussed in... | 2026-04-13 06:06:43 | 2026-04-27 15:32:30 | 2026-04-27 15:32:30 | null | CONTRIBUTOR | [] | null | null | null | null | ### Describe the bug
There is a change in the approach to decoding JSON types, added in https://github.com/huggingface/datasets/commit/d560b58e1f1ec96591a95a1780ee118f5eea6c74. Since 4.7.0, to_list() returns raw JSON strings for columns stored as Json(), while direct access via __getitem__ returns dicts.
In versions... | {
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https://api.github.com/repos/huggingface/datasets/issues/8129 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8129/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8129/comments | https://api.github.com/repos/huggingface/datasets/issues/8129/events | https://github.com/huggingface/datasets/issues/8129 | 4,241,704,875 | I_kwDODunzps7800er | 8,129 | `load_dataset()` hangs when `hf_xet` is enabled | {
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"Apologies, seems to have been a stale cache issue. Nuking the datasets cache fixed the issue"
] | 2026-04-10 21:00:24 | 2026-04-10 21:07:56 | 2026-04-10 21:07:56 | null | MEMBER | [] | null | null | null | null | ### Describe the bug
Hi! I am getting a peculiar download issue on the latest versions of `datasets` and `hfh` where datasets hang indefinitely:
```py
from datasets import load_dataset
load_dataset("openai/gsm8k", "main", split="test")
```
Note that:
- streaming=True works.
- Direct Hub access works.
- Th... | {
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https://api.github.com/repos/huggingface/datasets/issues/8125 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8125/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8125/comments | https://api.github.com/repos/huggingface/datasets/issues/8125/events | https://github.com/huggingface/datasets/issues/8125 | 4,223,104,906 | I_kwDODunzps77t3eK | 8,125 | Feature request: being able to disable chmod for flat permission filesystems | {
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"Context: the operation fails on GCS FUSE mounts, and likely will on similar s3-backed file systems.\n\n File \"/home/user/.venv/lib/python3.12/site-packages/datasets/arrow_dataset.py\", line 3747, in _map_single ... | 2026-04-08 08:17:14 | 2026-07-08 16:35:43 | null | null | NONE | [] | null | null | null | null | ### Feature request
For flat permission file systems, `os.chmod` simply fails when trying to cache datasets - in some places such as: https://github.com/huggingface/datasets/blob/main/src/datasets/arrow_dataset.py#L4043-L4048 for arrow datasets.
This seems to be optional to obtained desired behavior as simply comment... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8120 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8120/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8120/comments | https://api.github.com/repos/huggingface/datasets/issues/8120/events | https://github.com/huggingface/datasets/issues/8120 | 4,201,197,701 | I_kwDODunzps76aTCF | 8,120 | Patch fields truncated — missing trailing newlines | {
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"Hi, I'd like to work on this issue. I'll try to reproduce this issue and see where the newline is being stripped.",
"Hi @hetao-git\n\nI was able to reproduce this issue, I used the instance \"atlanhq_atlan-python_pr37\" from the AweAI-Team/Scale-SWE dataset. I observed that applying the GitHub patch (pull/37.dif... | 2026-04-03 16:07:47 | 2026-04-30 15:45:52 | 2026-04-30 15:45:52 | null | NONE | [] | null | null | null | null | Description: Multiple entries in the dataset have patches (test.patch and fix.patch) and f2p_patch fields with truncated content. The trailing blank lines that are part of valid unified diff format are stripped, causing git apply to fail with "corrupt patch" errors.
Affected instances (confirmed): atlanhq_atlan-python... | {
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https://api.github.com/repos/huggingface/datasets/issues/8116 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8116/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8116/comments | https://api.github.com/repos/huggingface/datasets/issues/8116/events | https://github.com/huggingface/datasets/issues/8116 | 4,197,189,620 | I_kwDODunzps76LAf0 | 8,116 | `to_json()` serializes `Json()` feature as escaped string instead of native JSON object | {
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"Hi! I ran into this issue as well, I think the root cause was that under `_batch_json()` of `JsonDatasetWriter` it was directly exporting the encoded string without decoding it first. I will try to add a PR with a small fix. ",
"#self-assign"
] | 2026-04-02 21:59:15 | 2026-04-10 13:12:51 | 2026-04-10 13:12:51 | null | CONTRIBUTOR | [] | null | null | null | null | ### Describe the bug
When a dataset column uses the `Json()` feature type, calling `to_json()` writes the value as an escaped JSON string (e.g., `"{\"cat_a\":1,\"cat_b\":2}"`) instead of a native JSON object (e.g., `{"cat_a":1,"cat_b":2}`).
This causes two problems:
1. The output JSON file is not interoperable with ... | {
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https://api.github.com/repos/huggingface/datasets/issues/8110 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8110/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8110/comments | https://api.github.com/repos/huggingface/datasets/issues/8110/events | https://github.com/huggingface/datasets/issues/8110 | 4,176,918,326 | I_kwDODunzps749rc2 | 8,110 | `set_format` resets features | {
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"couldn't replicate with: \n\n``` bash\nPlatform: macos\npython: 3.10.9\ndatasets: 4.8.4\nhuggingface_hub: 0.36.2\npyarrow: 23.0.1\npandas: 2.3.3\nfsspec: 2026.2.0\n\n```\n\n\n``` python\nimport datasets\nfrom datasets import Array2D, Dataset\nimport numpy as np\n\n# Create a dataset with Array2D feature\ndata = {\... | 2026-03-31 07:59:32 | 2026-05-11 07:15:16 | 2026-05-11 07:15:16 | null | NONE | [] | null | null | null | null | ### Describe the bug
Calling `dataset.set_format('...')` resets the informative features such as `Array2D` etc. back into `List(List(Value))` and so on.
### Steps to reproduce the bug
```py
>>> dataset.features
{'lld': Array2D(shape=(None, 26), dtype='float32')}
>>> dataset.set_format('torch')
>>> dataset.features
... | {
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https://api.github.com/repos/huggingface/datasets/issues/8085 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8085/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8085/comments | https://api.github.com/repos/huggingface/datasets/issues/8085/events | https://github.com/huggingface/datasets/issues/8085 | 4,120,101,624 | I_kwDODunzps71k8L4 | 8,085 | ImportError: cannot import name 'VideoReader' from 'torchvision.io' when using datasets with torch format | {
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"`datasets` 4.8.4 is out and includes a fix :)"
] | 2026-03-23 11:16:20 | 2026-03-23 14:23:25 | 2026-03-23 14:00:57 | null | NONE | [] | null | null | null | null | ### Describe the bug
For PyTorch 2.11 + torchvision 0.26.0 when using the datasets library and setting the format to "torch", an ImportError occurs because the datasets library attempts to import VideoReader from torchvision.io, but this object is not found in the installed torchvision version.
**Error message**:
> ... | {
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https://api.github.com/repos/huggingface/datasets/issues/8078 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8078/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8078/comments | https://api.github.com/repos/huggingface/datasets/issues/8078/events | https://github.com/huggingface/datasets/issues/8078 | 4,086,560,531 | I_kwDODunzps7zk_cT | 8,078 | Inconsistent loading of LFS-hosted files in Dangindev/viet-cultural-vqa dataset | {
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"I also have been stuck in same problem ",
"This should be fixed, thanks for reporting ! let us know if you ever encounter other issues in the future",
"It's okay. \n\nGood job, thanks your support! "
] | 2026-03-17 06:44:01 | 2026-03-30 04:14:29 | 2026-03-30 04:14:29 | null | NONE | [] | null | null | null | null | ### Describe the bug
Describe the bug
Some files in the Dangindev/viet-cultural-vqa dataset fail to load via the Hugging Face datasets library.
xet-hosted files load fine
LFS-hosted files sometimes fail
Example:
Fails: https://huggingface.co/datasets/Dangindev/viet-cultural-vqa/blob/main/images/am_thuc/banh_chung_T... | {
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https://api.github.com/repos/huggingface/datasets/issues/8075 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8075/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8075/comments | https://api.github.com/repos/huggingface/datasets/issues/8075/events | https://github.com/huggingface/datasets/issues/8075 | 4,085,618,908 | I_kwDODunzps7zhZjc | 8,075 | `.batch()` error on formatted datasets | {
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"Hi ! Good catch :) Since table-formatted iterable datasets have an Arrow path (i.e. they have `.iter_arrow()`) I guess a simple fix would be to make `.batch()` make the dataset arrow-formatted and use a `batch_arrow_fn` in that case (instead of the current `_batch_fn` that expects dictionaries). It would also be b... | 2026-03-17 01:08:13 | 2026-04-10 13:14:03 | 2026-04-10 13:14:03 | null | COLLABORATOR | [] | null | null | null | null | The `.batch()` method currently assumes the input (batch) is always a dictionary, which causes errors when it isn't. This can happen with formatted datasets, since formats like `"pyarrow"`, `"pandas"` (only affects `IterableDataset`), and `"polars"` return tables/dataframes instead of dictionaries.
For example:
```pyt... | {
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https://api.github.com/repos/huggingface/datasets/issues/8065 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8065/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8065/comments | https://api.github.com/repos/huggingface/datasets/issues/8065/events | https://github.com/huggingface/datasets/issues/8065 | 4,073,606,584 | I_kwDODunzps7yzk24 | 8,065 | ARM audio support broken | {
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"See also https://github.com/NVIDIA/garak/issues/1622#issuecomment-3937720381",
"Hi @leondz , thanks for the detailed bug report — the description and reproduction steps are really clear.\n\nI’d love to take a shot at investigating and potentially fixing this issue. Before I start digging into the codebase, I jus... | 2026-03-13 22:06:36 | 2026-09-08 16:04:10 | null | null | CONTRIBUTOR | [] | null | null | null | null | ### Describe the bug
`datasets` 4.0 moved to using `torchcodec` for audio datasets, which doesn't support ARM hardware under Linux and Windows
### Steps to reproduce the bug
try:
* Try to install `torchcodec` under Linux ARM64
or:
* Try to install `torchcodec` under Windows ARM64
or, on either of those platforms... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8052 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8052/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8052/comments | https://api.github.com/repos/huggingface/datasets/issues/8052/events | https://github.com/huggingface/datasets/issues/8052 | 4,041,972,911 | I_kwDODunzps7w65yv | 8,052 | [Security] Zip/Rar/7z Archive Extraction Path Traversal (Incomplete CVE-2007-4559 Mitigation) | {
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"Hi! I'm currently exploring the codebase and came across this issue. I'd be interested in investigating it further and trying to reproduce the behavior locally.\n\nIf no one is actively working on it, I'd be happy to take a look and attempt a fix.\n",
"The steps to reproduce don't cause any file extraction outsi... | 2026-03-08 19:09:32 | 2026-03-10 23:27:45 | 2026-03-10 23:27:45 | null | NONE | [] | null | null | null | null | ## Security Vulnerability Report
**Reporter:** Conner Webber (conner.webber000@gmail.com)
**Severity:** HIGH (CVSS 3.1: 8.2)
**CWE:** CWE-22 (Improper Limitation of a Pathname to a Restricted Directory)
## Summary
The `ZipExtractor`, `RarExtractor`, and `SevenZipExtractor` classes in `datasets/utils/extract.py` call... | {
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https://api.github.com/repos/huggingface/datasets/issues/8048 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8048/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8048/comments | https://api.github.com/repos/huggingface/datasets/issues/8048/events | https://github.com/huggingface/datasets/issues/8048 | 4,031,613,102 | I_kwDODunzps7wTYiu | 8,048 | Support 3D Datasets | {
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"Closing, as this got implemented in:\n\n[feat: add 3D mesh support and MeshFolder builder #8055](https://github.com/huggingface/datasets/pull/8055)\n\n[fix: embed_external_files=True for mesh support #8224](https://github.com/huggingface/datasets/pull/8224)"
] | 2026-03-06 01:23:08 | 2026-06-02 17:40:12 | 2026-06-02 17:38:55 | null | CONTRIBUTOR | [] | null | null | null | null | ### Feature request
In `datasets` library we have options to load `image` and `audio` datasets which can be viewed in the Dataset Viewer.
LIKE:
```bash
from datasets import load_dataset, Image
from datasets import load_dataset, Audio
```
> https://huggingface.co/docs/datasets/en/image_load & https://huggingface.co/do... | {
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https://api.github.com/repos/huggingface/datasets/issues/8046 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8046/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8046/comments | https://api.github.com/repos/huggingface/datasets/issues/8046/events | https://github.com/huggingface/datasets/issues/8046 | 4,030,348,328 | I_kwDODunzps7wOjwo | 8,046 | `Dataset.map()` with `num_proc > 1` fails when some shards produce `List(Value('null'))` (empty lists) | {
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"\n### Root cause\n\nIn `src/datasets/features/features.py`, both `_check_if_features_can_be_aligned` and `_align_features` use:\n\n```python\nisinstance(v, Value) and v.dtype == \"null\"\n```\n\nto check for null compatibility. However, `List(Value('null'))` is **not** an instance of `Value` — it's an instance of ... | 2026-03-05 20:12:13 | 2026-03-09 17:52:13 | 2026-03-09 17:52:13 | null | CONTRIBUTOR | [] | null | null | null | null | ### Describe the bug
When using `Dataset.map()` with `num_proc > 1`, if the map function produces a list column where some shards contain only empty lists `[]` and other shards contain non-empty lists of structs, the feature type inference is inconsistent across shards:
- Shards with only empty lists → `List(Value('n... | {
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https://api.github.com/repos/huggingface/datasets/issues/8034 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8034/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8034/comments | https://api.github.com/repos/huggingface/datasets/issues/8034/events | https://github.com/huggingface/datasets/issues/8034 | 4,004,188,523 | I_kwDODunzps7uqxFr | 8,034 | [BUG] load_datasets() cannot use the generated Arrow cache correctly | {
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"PYTHONHASHSEED=1 uv run python -c\n \"\nfrom datasets.load import LocalDatasetModuleFactory\nmod = LocalDatasetModuleFactory('/cache/datasets/imagenet-1k')\ndm = mod.get_module()\nprint('Hash:', dm.hash)\n\"\nResolving data files: 100%|█████████| 294/294 [00:00<00:00, 20584.68it/s]\nResolving data files: 100%|████... | 2026-02-28 08:11:23 | 2026-03-04 13:50:08 | null | null | CONTRIBUTOR | [] | null | null | null | null | ### Describe the bug
The datasets library cannot use the generated Arrow cache correctly, seemingly due to a flaw in the internal hash symbol calculation logic.
The following code provides verification.
I am trying to locate the specific code position, and if there are further developments, I will update here.
### S... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8029 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8029/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8029/comments | https://api.github.com/repos/huggingface/datasets/issues/8029/events | https://github.com/huggingface/datasets/issues/8029 | 4,001,742,455 | I_kwDODunzps7uhb53 | 8,029 | `cache_dir` option in `download_config` in `load_dataset` is not respected | {
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"Actually, I used debugger to step into the code of `datasets`, and found `load_dataset` calls into `cached_path`, where it calls into `hf_hub_download` method for `hf://` links:\nhttps://github.com/huggingface/datasets/blob/6e8eaeed4d202b72eff44ba1a9ec5b7d81d2d3e6/src/datasets/utils/file_utils.py#L182-L195\n\nSome... | 2026-02-27 16:05:30 | 2026-02-27 23:34:28 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
Downloaded files still go to `~/.cache/huggingface/hub/` even if I specified `cache_dir` option in `download_config` in `load_dataset`.
### Steps to reproduce the bug
Run my freshly written script and found that downloaded files did not go where I want.
```python
'''
下载OpenWebText数据集，允许使用代理
'''
... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8015 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8015/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8015/comments | https://api.github.com/repos/huggingface/datasets/issues/8015/events | https://github.com/huggingface/datasets/issues/8015 | 3,974,281,900 | I_kwDODunzps7s4rqs | 8,015 | Iterating a streaming dataset correctly in random order | {
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"Hi, reshuffling is actually pretty easy:\n\n```python\n\"\"\" shuffle.py \"\"\"\nfrom datasets import load_dataset\n\nnum_proc = 8 # tweak it here depending on your machine\nseed = 42\nds = load_dataset(\"jackyhate/text-to-image-2M\", num_proc=num_proc)\nds = ds.shuffle(seed=seed)\nds.push_to_hub(\"my-username/te... | 2026-02-22 11:34:06 | 2026-05-11 15:08:20 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
For training to work properly it is considered good practice in machine learning to sample the dataset randomly (uniformly). I am not sure how the user is expected to do it correctly when the creator of the dataset did a bad job.
https://huggingface.co/docs/hub/datasets-webdataset
```
**Shuffle*... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8012 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8012/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8012/comments | https://api.github.com/repos/huggingface/datasets/issues/8012/events | https://github.com/huggingface/datasets/issues/8012 | 3,963,855,875 | I_kwDODunzps7sQ6QD | 8,012 | HC3 dataset fails to load with datasets>=3 due to legacy script (HC3.py) | {
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"This is not a bug. This is intended behaviour. The only ways to resolve this are\n1. use the old `datasets` versions\n2. load the dataset and upload it to your own repo without a script\n3. raise an issue in the dataset and wait for the owner to update it."
] | 2026-02-19 16:27:51 | 2026-02-20 11:58:20 | 2026-02-20 11:58:20 | null | NONE | [] | null | null | null | null | ### Describe the bug
It looks like the current documentation suggests loading the dataset like this:
`load_dataset("Hello-SimpleAI/HC3", split="train")
`
But with datasets>=3.x, this raises:
RuntimeError: Dataset scripts are no longer supported, but found HC3.py
The dataset loads correctly if we specify the parqu... | {
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https://api.github.com/repos/huggingface/datasets/issues/8010 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8010/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8010/comments | https://api.github.com/repos/huggingface/datasets/issues/8010/events | https://github.com/huggingface/datasets/issues/8010 | 3,963,448,558 | I_kwDODunzps7sPWzu | 8,010 | audiofolder / folder-based loader rejects metadata.csv when file_name column is inferred as large_string | {
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"Proposing a PR for this [here](https://github.com/huggingface/datasets/pull/8011)\n\nPS: I didn't find a contributing documentation. Please recommend any changes in issue or PR if any. Thank you!"
] | 2026-02-19 15:06:09 | 2026-02-19 15:29:41 | 2026-02-19 15:29:41 | null | NONE | [] | null | null | null | null | ### Describe the bug
When loading a dataset with load_dataset("audiofolder", data_dir=...) and a metadata.csv (with a file_name column), loading can fail with:
`ValueError: file_name or *_file_name must be present as dictionary key (with type string) in metadata files`
even when the CSV clearly has a file_name colum... | {
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https://api.github.com/repos/huggingface/datasets/issues/8007 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8007/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8007/comments | https://api.github.com/repos/huggingface/datasets/issues/8007/events | https://github.com/huggingface/datasets/issues/8007 | 3,946,695,329 | I_kwDODunzps7rPcqh | 8,007 | Add option for loading audio with video | {
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"Hi,\nI’m interested in working on this issue.\n\nFrom what I understand, audio decoding would involve an AudioDecoder, and previous discussions have suggested handling it separately. I’d like to explore whether integrating audio extraction in relation to the current video decoding workflow would be appropriate, or... | 2026-02-16 09:11:02 | 2026-06-17 15:25:31 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
Currently, `torchcodec` don't allow extracting `Audio` from `Video` https://github.com/meta-pytorch/torchcodec/issues/1158, but when I upload videos with audio to hub using `videofolder`, then this is not possible to retrieve audio from it. Probably `VideoDecoder` can be extended with `audio` para... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8005 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8005/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8005/comments | https://api.github.com/repos/huggingface/datasets/issues/8005/events | https://github.com/huggingface/datasets/issues/8005 | 3,941,908,297 | I_kwDODunzps7q9L9J | 8,005 | Multi-channel audio is automatically cast to mono, num_channels is ignored | {
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"**Workaround**\nDirectly load audio using torchcodec, this is what datasets does under the hood (but doesn't maintain multi-channel)\n\n```python\nimport torchcodec\n\ndecoder = torchcodec.decoders.AudioDecoder(audio[\"bytes\"])\naudio_samples = decoder.get_all_samples()\n\naudio = audio_samples.data.numpy()\nsamp... | 2026-02-14 17:28:03 | 2026-02-25 15:17:18 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
The `num_channels` parameter in `datasets.Audio()` is documented to preserve stereo channels when set to `None` (preserve original) or `2` (explicit stereo), but it currently downmixes all audio to mono regardless of this setting.
### Steps to reproduce the bug
```python
import numpy as np
impor... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7999 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7999/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7999/comments | https://api.github.com/repos/huggingface/datasets/issues/7999/events | https://github.com/huggingface/datasets/issues/7999 | 3,915,367,642 | I_kwDODunzps7pX8Ta | 7,999 | Too many dataloader workers: 4 (max is dataset.num_shards=3). Stopping 1 dataloader workers. | {
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"Hi, thanks for the clear question and code snippet!\n\nFrom my understanding, **hf_dataset.num_shards** represents the number of actual iterable partitions that the streaming dataset can be read from in parallel. This is not the same as the number of underlying Parquet files—many files can be grouped into a much s... | 2026-02-09 09:26:37 | 2026-02-15 14:25:56 | null | null | NONE | [] | null | null | null | null | Hi !
I’m working on training with a large-scale dataset (100+ Parquet files) using lazy loading, and I’m struggling to understand/optimize the num_shards setting— in the lerobot repo: streaming_datasets.py:
```
from datasets import load_dataset
self.hf_dataset: datasets.IterableDataset = load_dataset(
self.... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7990 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7990/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7990/comments | https://api.github.com/repos/huggingface/datasets/issues/7990/events | https://github.com/huggingface/datasets/issues/7990 | 3,895,870,826 | I_kwDODunzps7oNkVq | 7,990 | Dataset.map crashes when first examples return None and later examples return dict — writer not initialized | {
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"map() expects a function that always return dict or that always return none",
"Hi, I'd like to work on this if the team is open to it.\n\nI understand from @lhoestq's comment that `map()` currently expects\na consistent return type. However, the crash with `AttributeError: \n'NoneType' object has no attribute 'w... | 2026-02-04 10:43:20 | 2026-05-26 19:09:11 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
I detected a serious [bug from datasets/arrow_dataset.py](https://github.com/huggingface/datasets/blob/main/src/datasets/arrow_dataset.py#L3676)
---
**Description of the bug**
`Dataset.map` crashes with `writer is None` when the map function returns `None` for the first few examples and a diction... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7986 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7986/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7986/comments | https://api.github.com/repos/huggingface/datasets/issues/7986/events | https://github.com/huggingface/datasets/issues/7986 | 3,892,776,651 | I_kwDODunzps7oBw7L | 7,986 | `Dataset.map()` causes cache miss/fingerprint change when closure captures self containing non-deterministic state. | {
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"I suggest metion this in docs specifically for attention with use, tell users explicitly to pass arguments with `fn_kwargs` param or using `functools.partial` to create a pure funcion."
] | 2026-02-03 19:16:49 | 2026-02-06 08:38:13 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
When using `.map()` with a function defined inside a **class (of which has any non-deterministic states)** method (a closure), if that function captures `self` to access a configuration variable (e.g., self.foo), the fingerprint mechanism serializes the entire class instance state.
If the class i... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7970 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7970/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7970/comments | https://api.github.com/repos/huggingface/datasets/issues/7970/events | https://github.com/huggingface/datasets/issues/7970 | 3,869,700,866 | I_kwDODunzps7mpvMC | 7,970 | cast_column(..., Audio) fails with load_dataset("csv",) | {
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"The following code *does* work:\n```py\nfrom datasets import load_dataset,Audio,Features\n\ndataset = load_dataset(\"csv\",data_files=\"audio.csv\",features=Features({\"audio\": Audio()}))\nprint(dataset[\"train\"][0][\"audio\"])\n```",
"Thanks for reporing ! Are you using pandas v3 by any chance ? The CSV loade... | 2026-01-29 09:33:35 | 2026-04-04 12:45:45 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
Attempt to load a dataset from a csv with a single `audio` column with a single row with a path to an audio file fails when casting the column to Audio, but the exact same dataset created from a dictionary succeeds.
### Steps to reproduce the bug
1. Have any valid audio file `audio.wav`
2. Have ... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7968 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7968/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7968/comments | https://api.github.com/repos/huggingface/datasets/issues/7968/events | https://github.com/huggingface/datasets/issues/7968 | 3,864,988,355 | I_kwDODunzps7mXwrD | 7,968 | Potential conflicting type checks and dead code in `/src/datasets/table.py` | {
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"ConcatenationTable is a subclass of datasets.table.Table but not pa.Table, so it should be fine",
"Hi! Triaging stale issues — I don't think this one is actually dead code; the premise is off.\n\nThe claim is that `isinstance(table, ConcatenationTable)` at line 4 is unreachable because the line-2 `isinstance(tab... | 2026-01-28 11:34:53 | 2026-05-11 11:04:04 | 2026-05-11 11:04:04 | null | NONE | [] | null | null | null | null | When statically analyzing and manually reviewing the code, I noticed a potential logic conflicting in `/src/datasets/table.py` as follows:
```
def to_blocks(table: Union[pa.Table, Table]) -> list[list[TableBlock]]:
if isinstance(table, pa.Table):
return [[InMemoryTable(table)]]
elif isinstance(ta... | {
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https://api.github.com/repos/huggingface/datasets/issues/7965 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7965/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7965/comments | https://api.github.com/repos/huggingface/datasets/issues/7965/events | https://github.com/huggingface/datasets/issues/7965 | 3,858,483,549 | I_kwDODunzps7l-8ld | 7,965 | `huggingface_hub.errors.HfHubHTTPError: 404 Client Error: Not Found for url` when fetching a dataset with `datasets.load_dataset` | {
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"Hi ! Yes you should use `cornell-movie-review-data/rotten_tomatoes` instead of `rotten_tomatoes`, which is the legacy name. Those datasets have been moved under their actual owners accounts some time ago (but we were keeping the old names as aliases)\n\nSome other impacted names are:\n- `imdb` -> `stanfordnlp/imdb... | 2026-01-27 02:20:31 | 2026-01-28 15:14:50 | 2026-01-28 15:14:50 | null | NONE | [] | null | null | null | null | Not a bug but a question. We started getting the following error:
https://github.com/mlflow/mlflow/actions/runs/21368603305/job/61506951617
```
ests/data/test_huggingface_dataset_and_source.py::test_from_huggingface_dataset_constructs_expected_dataset_with_revision - huggingface_hub.errors.HfHubHTTPError: 404 Client ... | {
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https://api.github.com/repos/huggingface/datasets/issues/7958 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7958/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7958/comments | https://api.github.com/repos/huggingface/datasets/issues/7958/events | https://github.com/huggingface/datasets/issues/7958 | 3,847,184,392 | I_kwDODunzps7lT2AI | 7,958 | [CUDA Tensors Not working in ~v4.5.0] set_format(type="torch", device="cuda") returns cpu | {
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"@lhoestq tagging you here as you were on the previous issue, hope that's fine. ",
"Thanks for reporting, let me take a look",
"I reverted this change which caused the issue #7961 , I'll do a new release soon but in the meantime feel free to install `datasets` from source",
"@lhoestq thanks a lot. I am actual... | 2026-01-23 12:06:48 | 2026-03-04 13:17:28 | 2026-03-04 13:17:28 | null | NONE | [] | null | null | null | null | ### Describe the bug
The problem is that when calling:
```ds.set_format(type="torch", columns = ["input", "labels"], device="cuda")```
The device type of the individual datapoints is now: `cpu` as opposed to `cuda:0`.
With `v4.0.0` it still works. With `v4.5.0` it doesn't work anymore.
Related Issue:
https://github... | {
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https://api.github.com/repos/huggingface/datasets/issues/7956 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7956/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7956/comments | https://api.github.com/repos/huggingface/datasets/issues/7956/events | https://github.com/huggingface/datasets/issues/7956 | 3,839,082,498 | I_kwDODunzps7k08AC | 7,956 | Is the 10k files / folder limit a hard limit for a dataset repo? | {
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"Yes, that's a hard limit. Can you split your files into different folders? Or we'll probably have a new repo type in the near to mid future that will relax this limit a bit. ",
"Thanks! Working around this with a different sharding parameter to have fewer overall fragments (and therefore fewer files in `*.lance/... | 2026-01-21 16:37:38 | 2026-01-22 09:38:38 | null | null | NONE | [] | null | null | null | null | ### Feature request
Can the hard limit of 10k files per folder be extended with acceptable loss in performance?
### Motivation
I'm uploading a lance dataset to huggingface hub and have a folder inside lance internals (`data/*.lance/_transactions`) that has > 20k atomic transaction records and my commits are being re... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7954 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7954/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7954/comments | https://api.github.com/repos/huggingface/datasets/issues/7954/events | https://github.com/huggingface/datasets/issues/7954 | 3,837,020,089 | I_kwDODunzps7ktEe5 | 7,954 | all_exhausted_without_replacement working same as first_exhausted | {
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"https://github.com/huggingface/datasets/pull/7955",
"it was fixed by https://github.com/huggingface/datasets/pull/7955"
] | 2026-01-21 07:50:31 | 2026-03-23 14:03:13 | 2026-03-23 14:03:13 | null | CONTRIBUTOR | [] | null | null | null | null | ### Describe the bug
>>> from datasets import Dataset, interleave_datasets
>>> d1 = Dataset.from_dict({"a": [0, 1, 2]})
>>> d2 = Dataset.from_dict({"a": [10, 11, 12, 13]})
>>> d3 = Dataset.from_dict({"a": [20, 21, 22]})
>>> dataset = interleave_datasets([d1, d2, d3], stopping_strategy="all_exhausted_without_replacemen... | {
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https://api.github.com/repos/huggingface/datasets/issues/7946 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7946/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7946/comments | https://api.github.com/repos/huggingface/datasets/issues/7946/events | https://github.com/huggingface/datasets/issues/7946 | 3,817,678,454 | I_kwDODunzps7jjSZ2 | 7,946 | Question: Is there a faster way to push_to_hub for large image datasets? | {
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"This is a really interesting approach, especially combining parallel parquet\nconversion with upload_large_folder and hf_xet.\n\nOne question / observation:\nThe shard calculation currently uses max_shard_size_mb as a proxy for\nsamples_per_shard. Since sample size can vary a lot across datasets,\nwould it make se... | 2026-01-15 13:54:37 | 2026-01-17 13:27:20 | null | null | NONE | [] | null | null | null | null | # Question: Is there a faster way to `push_to_hub` for large image datasets? Or could this approach be integrated?
Hi! I frequently work with large image datasets (100k-300k+ samples) and found that `dataset.push_to_hub()` can be quite slow.
cc @lhoestq - would love your thoughts on this!
I experimented with an alte... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7936 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7936/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7936/comments | https://api.github.com/repos/huggingface/datasets/issues/7936/events | https://github.com/huggingface/datasets/issues/7936 | 3,795,750,271 | I_kwDODunzps7iPo1_ | 7,936 | _add_retries_to_file_obj_read_method makes file_obj invalid for pyarrow | {
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"hmm not sure how to fix this, I believe `file_obj.__getattr__ = lambda _, attr: getattr(orig_file_obj, attr)` would make all the methods point to the original file_obj",
"> hmm not sure how to fix this, I believe `file_obj.__getattr__ = lambda _, attr: getattr(orig_file_obj, attr)` would make all the methods poi... | 2026-01-09 07:05:25 | 2026-01-14 13:47:50 | 2026-01-13 13:38:03 | null | NONE | [] | null | null | null | null | ### Describe the bug
I'm trying to use `load_dataset` to construct a dataset that read parquet data on HDFS streamingly, like
```python
ds = load_dataset(
"parquet",
data_files={
"train": "hdfs://xxx/train*.parquet",
"test": "hdfs://xxx/test*.parquet"
},
streaming=True,
)
```
I encounte... | {
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https://api.github.com/repos/huggingface/datasets/issues/7931 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7931/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7931/comments | https://api.github.com/repos/huggingface/datasets/issues/7931/events | https://github.com/huggingface/datasets/issues/7931 | 3,777,662,799 | I_kwDODunzps7hKo9P | 7,931 | Enable CORS + HTTP Range support for browser partial reads on cas-bridge.xethub.hf.co (Parquet row-group access) | {
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"Cc @assafvayner maybe ? or @cfahlgren1 @severo if you've already encountered this ?",
"OK, reproduced with hyparquet on https://huggingface.co/spaces/hyperparam/hyperparam, see https://huggingface.co/spaces/hyperparam/hyperparam?url=https%3A%2F%2Fhuggingface.co%2Fdatasets%2Ffacebook%2Fresearch-plan-gen%2Fblob%2F... | 2026-01-03 04:23:54 | 2026-02-24 21:31:37 | 2026-02-24 16:35:44 | null | NONE | [] | null | null | null | null | ### Feature request
## Summary
Browser-based data tools need Range requests to read Parquet efficiently (footer + selected row groups). Downloads from the Hub redirect to cas-bridge.xethub.hf.co (Xet bridge). The redirected host fails CORS preflight for Range/HEAD workflows, blocking partial reads. ([Hugging Face](htt... | {
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https://api.github.com/repos/huggingface/datasets/issues/7928 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7928/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7928/comments | https://api.github.com/repos/huggingface/datasets/issues/7928/events | https://github.com/huggingface/datasets/issues/7928 | 3,775,842,185 | I_kwDODunzps7hDseJ | 7,928 | `load_dataset` `revision` param not respected when fetching from cache | {
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"This might be better placed as a feature request not a bug, since the logging `Using the latest cached version of the dataset since sentientfutures/ahb couldn't be found on the Hugging Face Hub` is clear.",
"https://github.com/huggingface/datasets/pull/7929 This only solves the case of invalid revisions. Fetchin... | 2026-01-02 08:20:47 | 2026-04-17 16:01:16 | null | null | CONTRIBUTOR | [] | null | null | null | null | ### Describe the bug
`datasets.load_dataset` `revision` semantics are a bit inconsistent when the dataset is not found on the huggingface hub. When fetching the latest cached version of the dataset, the `revision` argument is ignored, so long as any cached versions of the dataset already exist in the HF cache.
### St... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7927 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7927/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7927/comments | https://api.github.com/repos/huggingface/datasets/issues/7927/events | https://github.com/huggingface/datasets/issues/7927 | 3,775,302,438 | I_kwDODunzps7hBosm | 7,927 | Using Stateful Dataloader with Split Dataset By Node and DCP for DDP | {
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"Does it need to be pickled?\n\n```python\n def load_state_dict(self, state_dict):\n hf_state = pickle.loads(state_dict[\"data\"])\n self.train_dataset.load_state_dict(hf_state)\n\n def state_dict(self):\n return {\"data\": pickle.dumps(self.train_dataset.state_dict())}\n```",
"Pickling... | 2026-01-01 22:27:07 | 2026-02-01 06:13:30 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
I am trying to determine how to save and load the Stateful Dataloader State with DCP and Split Dataset by Node for DDP.
Currently, I am running into the issue where I am receiving a slow resume.
```
Neither dataset nor iter(dataset) defines state_dict/load_state_dict so we are naively fast-forwar... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7922 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7922/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7922/comments | https://api.github.com/repos/huggingface/datasets/issues/7922/events | https://github.com/huggingface/datasets/issues/7922 | 3,772,247,021 | I_kwDODunzps7g1-vt | 7,922 | Support Apache TsFile Datasets | {
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"A large quantity of industrial timeseries data has been stored as TsFile, and I have been constantly hearing about AI fellows complaining about the lack of data or the insufficiency of data quality.\n\nI like the ambition that uses TsFile as the bridge between AI research and industrial analysis requirements. This... | 2025-12-31 08:07:51 | 2026-06-01 10:14:53 | 2026-06-01 10:14:53 | null | NONE | [] | null | null | null | null | ### Feature request
I would love to use Hugging Face datasets library to directly load datasets composed of .tsfile files, for example:
`ds = load_dataset("username/dataset-with-tsfile-files")`
This feature would allow researchers working on time-series tasks to seamlessly integrate datasets stored in the Apache TsF... | {
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https://api.github.com/repos/huggingface/datasets/issues/7918 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7918/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7918/comments | https://api.github.com/repos/huggingface/datasets/issues/7918/events | https://github.com/huggingface/datasets/issues/7918 | 3,765,489,462 | I_kwDODunzps7gcM82 | 7,918 | datasets.load_from_disk doesn't show progress bar | {
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"#self-assign"
] | 2025-12-28 09:14:41 | 2026-01-16 14:44:50 | 2026-01-16 14:44:50 | null | NONE | [] | null | null | null | null | ### Describe the bug
This is the inverse of the bug at [https://github.com/huggingface/datasets/issues/7030](https://github.com/huggingface/datasets/issues/7030), i.e. that `datasets.load_from_disk(path)` displays no progress bar. My dataset has > 16 files in it.
I am redirecting stdout as I capture the log, could th... | {
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https://api.github.com/repos/huggingface/datasets/issues/7917 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7917/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7917/comments | https://api.github.com/repos/huggingface/datasets/issues/7917/events | https://github.com/huggingface/datasets/issues/7917 | 3,764,913,807 | I_kwDODunzps7gaAaP | 7,917 | IterableDataset supports automatic sharding | {
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"You can already use `.shard()` instead like this:\n\n```python\ndataset = dataset.shard(index=rank, num_shards=world_size)\n```\n\nnote that it requires that `dataset.num_shards >= world_size`, and that it may result in nodes having the same number of shards +- 1",
"> You can already use `.shard()` instead like ... | 2025-12-27 16:48:29 | 2025-12-29 16:06:52 | null | null | NONE | [] | null | null | null | null | ### Feature request
Added sharding function support to the streaming IterableDataset, allowing users to adjust the number of shards according to their training resources. For example:
```
dataset = load_dataset(*, stream=True)
dataset = dataset.shard(num_shards=num_shards, num_samples=num_samples) #We may need to know... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7915 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7915/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7915/comments | https://api.github.com/repos/huggingface/datasets/issues/7915/events | https://github.com/huggingface/datasets/issues/7915 | 3,762,042,396 | I_kwDODunzps7gPDYc | 7,915 | GDPval dataset Word docs corrupted | {
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"tentatively tagging @simonpfish ^\n\n(if it's an option you could enable PRs/Discussions on your dataset on HF)"
] | 2025-12-25 13:56:55 | 2025-12-26 09:06:13 | null | null | NONE | [] | null | null | null | null | The [openai/gdpval](https://huggingface.co/datasets/openai/gdpval) dataset on Hugging Face contains Word .docx files with two types of corruption that cause Microsoft Word to display an "unreadable content" error.
### Root Causes
1. **Corrupted settings.xml**: The `word/settings.xml` file uses incorrect namespace pre... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7914 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7914/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7914/comments | https://api.github.com/repos/huggingface/datasets/issues/7914/events | https://github.com/huggingface/datasets/issues/7914 | 3,760,894,100 | I_kwDODunzps7gKrCU | 7,914 | [ROCm] please install 'torchcodec' | {
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"I was able to install torchcodec by building it from source and have put together a PR: https://github.com/vllm-project/vllm/pull/31323\n\nStill I think it would make this framework more robust to add at least one fallback lib (that is more widely used) in place should torchcodec installation fail or library is no... | 2025-12-24 19:39:17 | 2026-03-04 10:18:33 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
Datasets library is widely used by many Python packages. Naturally, it is a requirement on many platforms. This includes vLLM for ROCm. During audio dataset tests, there is an exception triggered:
```python
def decode_example(
self, value: dict, token_per_repo_id: Optional[dict[str, Un... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7905 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7905/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7905/comments | https://api.github.com/repos/huggingface/datasets/issues/7905/events | https://github.com/huggingface/datasets/issues/7905 | 3,734,233,245 | I_kwDODunzps7ek-Cd | 7,905 | Unbounded network usage when opening Data Studio | {
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"cc @cfahlgren1",
"Thanks for reporting! Looking into this!",
"This should be fixed. Thank you for your patience! 🤗"
] | 2025-12-16 10:45:02 | 2026-01-06 15:04:43 | 2026-01-06 15:04:43 | null | NONE | [] | null | null | null | null | ### Describe the bug
Opening the Data Studio tab on a dataset page triggers continuous and unbounded network traffic. This issue occurs across multiple browsers and continues even without user interaction.
### Steps to reproduce the bug
https://huggingface.co/datasets/slone/nllb-200-10M-sample/viewer
### Expected... | {
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https://api.github.com/repos/huggingface/datasets/issues/7904 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7904/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7904/comments | https://api.github.com/repos/huggingface/datasets/issues/7904/events | https://github.com/huggingface/datasets/issues/7904 | 3,727,978,498 | I_kwDODunzps7eNHAC | 7,904 | Request: Review pending neuroimaging PRs (#7886 BIDS loader, #7887 lazy loading) | {
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"Hi ! sure I'll be happy to take a look, sorry for the delay :)"
] | 2025-12-14 20:34:31 | 2025-12-15 11:25:29 | null | null | CONTRIBUTOR | [] | null | null | null | null | ## Summary
I'm building production neuroimaging pipelines that depend on `datasets` and would benefit greatly from two pending PRs being reviewed/merged.
## Pending PRs
| PR | Description | Status | Open Since |
|----|-------------|--------|------------|
| [#7886](https://github.com/huggingface/datasets/pull/7886) |... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7902 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7902/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7902/comments | https://api.github.com/repos/huggingface/datasets/issues/7902/events | https://github.com/huggingface/datasets/issues/7902 | 3,723,281,150 | I_kwDODunzps7d7ML- | 7,902 | The child process retrieves the dataset directly from the main process instead of executing `memory_mapped_arrow_table_from_file`. | {
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"Memory mapping is actually the way for processes to share memory efficiently and without copy. It is efficient when on are using a local disk, and it's discouraged to use it on remote disk for the reasons you observed.\n\nWhat you can do instead is save the dataset as Parquet on your remote storage (or on Hugging ... | 2025-12-12 12:37:44 | 2025-12-15 11:48:16 | null | null | NONE | [] | null | null | null | null | ### Feature request
The child process retrieves the dataset directly from the main process instead of executing `memory_mapped_arrow_table_from_file`.
### Motivation
Because my local disk space is insufficient, I can only store a dataset on a remote Ceph server and process it using datasets.
I used the data-juicer[h... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7901 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7901/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7901/comments | https://api.github.com/repos/huggingface/datasets/issues/7901/events | https://github.com/huggingface/datasets/issues/7901 | 3,722,243,543 | I_kwDODunzps7d3O3X | 7,901 | ShuffledDataSourcesArrowExamplesIterable cannot properly resume from checkpoint | {
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"Hi ! As you can read in the logs, the shuffle buffer content is lost when resuming a shuffled dataset. The default size is 1000 examples, but you can tweak it\n\ne.g. if you run your code with this\n\n```diff\n- ds = Dataset.from_dict({\"a\": range(12)}).to_iterable_dataset(num_shards=1)\n- ds = ds.shuffle(seed=42... | 2025-12-12 06:57:32 | 2026-08-12 22:09:19 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
ShuffledDataSourcesArrowExamplesIterable cannot properly resume from checkpoint
### Steps to reproduce the bug
1. The reproducible code is as follows：
```
from datasets import Dataset, concatenate_datasets, interleave_datasets
ds = Dataset.from_dict({"a": range(12)}).to_iterable_dataset(num_sha... | null | {
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