Datasets:
Duplicate from IFM/Code-Reasoning
Browse filesCo-authored-by: Kevin Zhou <zhou94539@users.noreply.huggingface.co>
This view is limited to 50 files because it contains too many changes. See raw diff
- .gitattributes +60 -0
- README.md +132 -0
- code-no-thinking-hard/code_solutions_no_reasoning_8k-hard_clean_oss_removal.chunk0-aa9ce462ac-00000.parquet +3 -0
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- code-no-thinking-hard/code_solutions_no_reasoning_8k-hard_clean_oss_removal.chunk0-aa9ce462ac-00047.parquet +3 -0
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README.md
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---
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license: apache-2.0
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task_categories:
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- text-generation
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tags:
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- k2-horizon
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- training-data
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- parquet
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- code
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- reasoning
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configs:
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- config_name: code-no-thinking
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data_files:
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- split: train
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path: code-no-thinking/*.parquet
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- config_name: code-no-thinking-hard
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data_files:
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- split: train
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path: code-no-thinking-hard/*.parquet
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- config_name: code-thinking-v1
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data_files:
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- split: train
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path: code-thinking-v1/*.parquet
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- config_name: code-thinking-hard
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data_files:
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- split: train
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path: code-thinking-hard/*.parquet
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- config_name: code-thinking-v0
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data_files:
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- split: train
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path: code-thinking-v0/*.parquet
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- config_name: codeio
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data_files:
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- split: train
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path: codeio/*.parquet
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- config_name: code-task-synthesis
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data_files:
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- split: train
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path: code-task-synthesis/*.parquet
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---
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# Code-Reasoning
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## Dataset Description
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| 45 |
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Code problem-solving data with reasoning, direct-answer, and task-synthesis subsets. This repository is part of the [K2 Horizon collection](https://huggingface.co/collections/IFM/k2-horizon).
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The repository is organized into multiple subsets. Every subset has a `train` split backed by Parquet shards, which supports Dataset Viewer inspection and streaming access.
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## K2 Horizon Dataset Series
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| Dataset repository | Focus | Subsets |
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| 53 |
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| -------------------------------------------------------------------------------- | ---------------------------------------- | ------: |
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| 54 |
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| [IFM/TxT360-v2](https://huggingface.co/datasets/IFM/TxT360-v2) | Web and question-answering text | 3 |
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| 55 |
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| [IFM/Code-Reasoning](https://huggingface.co/datasets/IFM/Code-Reasoning) | Code reasoning and task synthesis | 7 |
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| 56 |
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| [IFM/Math-Reasoning](https://huggingface.co/datasets/IFM/Math-Reasoning) | Mathematical reasoning and dialogue | 5 |
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| 57 |
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| [IFM/SFT-Reasoning](https://huggingface.co/datasets/IFM/SFT-Reasoning) | Instruction following and SFT-style data | 2 |
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| 58 |
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| [IFM/Pretrain-Behaviors](https://huggingface.co/datasets/IFM/Pretrain-Behaviors) | Behavior-focused pretraining data | 7 |
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| 59 |
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| 60 |
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## Dataset Subsets
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| 61 |
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| 62 |
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| Subset | Data files |
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| 63 |
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| ----------------------- | --------------------------------- |
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| 64 |
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| `code-no-thinking` | `code-no-thinking/*.parquet` |
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| 65 |
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| `code-no-thinking-hard` | `code-no-thinking-hard/*.parquet` |
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| 66 |
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| `code-thinking-v1` | `code-thinking-v1/*.parquet` |
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| 67 |
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| `code-thinking-hard` | `code-thinking-hard/*.parquet` |
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| 68 |
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| `code-thinking-v0` | `code-thinking-v0/*.parquet` |
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| 69 |
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| `codeio` | `codeio/*.parquet` |
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| 70 |
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| `code-task-synthesis` | `code-task-synthesis/*.parquet` |
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| 71 |
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| 72 |
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## Repository Structure
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| 73 |
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| 74 |
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```text
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| 75 |
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README.md
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| 76 |
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code-no-thinking/
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| 77 |
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<source-file>-<stable-id>-00000.parquet
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| 78 |
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<source-file>-<stable-id>-00001.parquet
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| 79 |
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code-no-thinking-hard/
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| 80 |
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<source-file>-<stable-id>-00000.parquet
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| 81 |
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<source-file>-<stable-id>-00001.parquet
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| 82 |
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code-thinking-v1/
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| 83 |
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<source-file>-<stable-id>-00000.parquet
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| 84 |
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<source-file>-<stable-id>-00001.parquet
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| 85 |
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code-thinking-hard/
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| 86 |
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<source-file>-<stable-id>-00000.parquet
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| 87 |
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<source-file>-<stable-id>-00001.parquet
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| 88 |
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code-thinking-v0/
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| 89 |
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<source-file>-<stable-id>-00000.parquet
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| 90 |
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<source-file>-<stable-id>-00001.parquet
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| 91 |
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codeio/
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| 92 |
+
<source-file>-<stable-id>-00000.parquet
|
| 93 |
+
<source-file>-<stable-id>-00001.parquet
|
| 94 |
+
code-task-synthesis/
|
| 95 |
+
<source-file>-<stable-id>-00000.parquet
|
| 96 |
+
<source-file>-<stable-id>-00001.parquet
|
| 97 |
+
```
|
| 98 |
+
|
| 99 |
+
The shard prefix is derived from the source JSONL filename and a stable identifier. Updating one source JSONL file replaces only that file's Parquet shards.
|
| 100 |
+
|
| 101 |
+
## Data Fields
|
| 102 |
+
|
| 103 |
+
Records originate as JSON objects and are converted to Parquet for release. Field names and nested structures can differ by subset. Inspect `features` before building a processing pipeline:
|
| 104 |
+
|
| 105 |
+
```python
|
| 106 |
+
from datasets import load_dataset
|
| 107 |
+
|
| 108 |
+
dataset = load_dataset(
|
| 109 |
+
"IFM/Code-Reasoning",
|
| 110 |
+
"code-no-thinking",
|
| 111 |
+
split="train",
|
| 112 |
+
streaming=True,
|
| 113 |
+
)
|
| 114 |
+
print(dataset.features)
|
| 115 |
+
print(next(iter(dataset)))
|
| 116 |
+
```
|
| 117 |
+
|
| 118 |
+
## Data Provenance and Processing
|
| 119 |
+
|
| 120 |
+
Individual subsets may have undergone source-specific filtering, cleaning, deduplication, quality scoring, or synthetic-data generation. Users should evaluate each subset for their target use case and inspect the available provenance metadata.
|
| 121 |
+
|
| 122 |
+
## Intended Use
|
| 123 |
+
|
| 124 |
+
This dataset is intended for language-model training and research. The subsets can be streamed independently, combined with user-defined sampling weights, or inspected through the Hugging Face Dataset Viewer.
|
| 125 |
+
|
| 126 |
+
## Limitations and Responsible Use
|
| 127 |
+
|
| 128 |
+
Large-scale training data can contain factual errors, duplicated material, sensitive topics, stereotypes, unsafe content, and other artifacts. Dataset users are responsible for performing evaluations, risk assessment, and filtering appropriate to their application.
|
| 129 |
+
|
| 130 |
+
## License and Terms of Use
|
| 131 |
+
|
| 132 |
+
This dataset is licensed under the Apache License 2.0 available at https://www.apache.org/licenses/LICENSE-2.0.
|
code-no-thinking-hard/code_solutions_no_reasoning_8k-hard_clean_oss_removal.chunk0-aa9ce462ac-00000.parquet
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| 1 |
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