morningstarxcdcode's picture
|
download
raw
1.57 kB
metadata
license: apache-2.0
tags:
  - text-dataset
  - pretraining
  - llm
  - fineweb
  - cosmopedia
  - math

Base LLM 400M

Self-mined multi-modal pretraining corpus targeting 200B tokens of high-quality text, video, audio, and image data.

Structure

  • data/shards/shard_{idx:08d}.bin — raw uint32 token IDs, ~128MB per shard
  • data/shards/shard_{idx:08d}.meta.json — 18-field sidecar with quality stats
  • state/ — runtime checkpoints (.state extension)

18-field sidecar schema

Field Type Description
shard_idx int Shard number
filename str Filename
num_tokens int Token count
dtype str uint32
size_bytes int File size
created_at str ISO 8601 timestamp
tokens int Token count (duplicate for compatibility)
avg_score float Mean quality score
min_score float Min quality score
max_score float Max quality score
std_score float Std dev of quality scores
n_above_3 int Chunks with score > 3.0
n_above_5 int Chunks with score > 5.0
score_hist dict 21-bin histogram (0.0–10.0 step 0.5)
modality_comp dict Modality composition counts
pillar_comp dict Pillar composition counts
ts float Unix timestamp
modality str Primary modality

Loading (Python)

from datasets import load_dataset
ds = load_dataset("morningstarxcdcode/base-llm-400m", split="train", streaming=True)
for example in ds:
    print(example["tokens"])

Xet Storage Details

Size:
1.57 kB
·
Xet hash:
991feadcfa77a7b6a605321fe7d8478eaf143dda89cddcfaf721b27c219b5d08

Xet efficiently stores files, intelligently splitting them into unique chunks and accelerating uploads and downloads. More info.