File size: 1,353 Bytes
f76d597 065df47 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 |
---
dataset_info:
features:
- name: content
dtype: string
- name: score
dtype: float64
- name: source
dtype: string
splits:
- name: train
num_bytes: 4041572884
num_examples: 1010925
download_size: 2339968968
dataset_size: 4041572884
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Sampling Code
```py
from typing import List
from datasets import Dataset, load_dataset
from tqdm import tqdm
TARGET_CHARS = 4_000_000_000
BUFFER_SIZE = 100_000
SEED = 42
HF_REPO = "sumuks/Ultra-FineWeb-1B"
def sample_fineweb(
target_chars: int = TARGET_CHARS,
buffer_size: int = BUFFER_SIZE,
seed: int = SEED,
) -> Dataset:
"""Return a random Ultra‑FineWeb sample meeting ``target_chars`` length."""
stream = load_dataset("openbmb/Ultra-FineWeb", split="en", streaming=True)
stream = stream.shuffle(seed=seed, buffer_size=buffer_size)
picked: List[dict] = []
char_count = 0
for row in tqdm(stream, desc="sampling"):
text = row["content"]
char_count += len(text)
picked.append(row)
if char_count >= target_chars:
break
return Dataset.from_list(picked)
if __name__ == "__main__": # pragma: no cover – CLI entry‑point
ds = sample_fineweb()
ds.push_to_hub(HF_REPO, private=False)
```
|