|
--- |
|
dataset_info: |
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features: |
|
- name: text |
|
dtype: string |
|
- name: id |
|
dtype: string |
|
- name: dump |
|
dtype: string |
|
- name: url |
|
dtype: string |
|
- name: date |
|
dtype: string |
|
- name: file_path |
|
dtype: string |
|
- name: language |
|
dtype: string |
|
- name: language_score |
|
dtype: float64 |
|
- name: token_count |
|
dtype: int64 |
|
splits: |
|
- name: train |
|
num_bytes: 51073574.99634302 |
|
num_examples: 14874 |
|
download_size: 30919243 |
|
dataset_size: 51073574.99634302 |
|
configs: |
|
- config_name: default |
|
data_files: |
|
- split: train |
|
path: data/train-* |
|
license: odc-by |
|
task_categories: |
|
- text-generation |
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language: |
|
- en |
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size_categories: |
|
- 10K<n<100K |
|
--- |
|
|
|
# FineWeb 10MT |
|
Roughly 10 million tokens worth of English FineWeb data. Obtained by taking the [10BT Sample](https://huggingface.co/datasets/HuggingFaceFW/fineweb/viewer/sample-10BT) of [FineWeb](https://huggingface.co/datasets/HuggingFaceFW/fineweb), shuffling it, sharding into 1000 shards, and selecting the first shard. |
|
|
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## Code |
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To reproduce FineWeb 10MT, simply use the following: |
|
|
|
```python |
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from datasets import load_dataset |
|
|
|
fineweb = load_dataset("HuggingFaceFW/fineweb", "sample-10BT", split="train").shuffle().shard(num_shards=1000, index=0) |
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|
|
token = "token" |
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fineweb.push_to_hub("OxxoCodes/fineweb-10MT", token=token) |
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``` |
