Datasets:
Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
pa_table = paj.read_json(
io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
)
File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
return check_status(status)
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: JSON parse error: Column() changed from object to string in row 0
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 101, in _split_generators
pa_table = next(iter(self._generate_tables(**splits[0].gen_kwargs, allow_full_read=False)))[1]
~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 304, in _generate_tables
batch = json_encode_fields_in_json_lines(original_batch, json_field_paths)
File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 111, in json_encode_fields_in_json_lines
examples = [ujson_loads(line) for line in original_batch.splitlines()]
~~~~~~~~~~~^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 20, in ujson_loads
return pd.io.json.ujson_loads(*args, **kwargs)
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
ValueError: Expected object or value
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 68, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
S-SALAAD — teacher logits & model releases
Open artifacts for the S-SALAAD compression project: the offline distillation data its models pre-train on, and the resulting checkpoints.
S-SALAAD/
├── logits/ teacher-logit distillation dataset
└── models/ model releases, indexed in models/README.md
logits/ — offline pre-training distillation data
| Teacher | nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-NVFP4 |
| Tokenizer | nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-NVFP4 |
| Source corpus | HuggingFaceFW/fineweb-edu |
Per-chunk schema (SafeTensors)
| Tensor | Dtype | Shape |
|---|---|---|
input_ids |
int32 | [R, T] |
top_idx |
int32 | [R, T, K] |
top_logprob |
float16 | [R, T, K] |
gold_logprob |
float16 | [R, T] |
where R = num_rows_in_chunk, T = 512, K = 10.
Each *.safetensors file has a sibling *.meta.json with the source shard,
chunk index, and the header fields above. logits/manifest.json lists every
committed chunk once the run is finalized.
Reading a chunk
import json, pathlib
from huggingface_hub import snapshot_download
from safetensors import safe_open
root = pathlib.Path(snapshot_download(
"egretwAlker/S-SALAAD", repo_type="dataset",
allow_patterns=["logits/*"],
))
manifest = json.loads((root / "logits" / "manifest.json").read_text())
for stem in manifest["chunks"]:
with safe_open(root / "logits" / f"{stem}.safetensors", framework="pt") as f:
input_ids = f.get_tensor("input_ids") # int32 [R, T]
top_idx = f.get_tensor("top_idx") # int32 [R, T, K]
top_logprob = f.get_tensor("top_logprob") # fp16 [R, T, K]
gold_logprob = f.get_tensor("gold_logprob") # fp16 [R, T]
models/ — model releases
Models pre-trained against these logits: dense baselines, low-rank ablations
and S-SALAAD models, where each linear layer is W = L + S (L low-rank, S
sparse).
models/<model>/
├── dense/
├── low-rank/
└── s-salaad/<variant>/ b8 … b64, unstructured, rowcol, nm-2-4
├── model.pth torch.save dict
└── model_config.json architecture
qwen3-1.7b/s-salaad/b64/ also has deployed versions: checkpoint/ beside one
p<N>m/ per N-million parameter budget. Each folder's README gives the
structure of its model.pth.
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