1.0
Datasets
All datasets matching “1.0”dclm-baseline-1.0
DCLM-baseline
DCLM-baseline is a 4T token / 3B document pretraining dataset that achieves strong performance on language model benchmarks.
Below are comparisions of model trained on DCLM-baseline with other models in the 7B regime.
Model
Params
Tokens
Open dataset?
CORE
MMLU
EXTENDED
Open weights, closed datasets
Llama2
7B
2T
✗
49.2
45.8
34.1
DeepSeek
7B
2T
✗
50.7
48.5
35.3
Mistral-0.3
7B
?
✗
57.0
62.7
45.1
QWEN-2
7B
?
✗
57.5
71.9
50.5
Llama3
8B
15T
✗… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations/dclm-baseline-1.0.droid_1.0.1This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "Franka",
"total_episodes": 95600,
"total_frames": 27612581,
"total_tasks": 0,
"total_videos": 286800,
"total_chunks": 95,
"chunks_size": 1000,
"fps": 15,
"splits": {
"train": "0:95600"
},
"data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/cadene/droid_1.0.1.essential-web-v1.0
🌐 Essential-Web: Complete 24-Trillion Token Dataset
🏆 Website | 🖥️ Code | 📖 Paper | ☁️ AWS
📋 Dataset Description
Essential-Web is a 24-trillion-token web dataset with document-level metadata designed for flexible dataset curation. The dataset provides metadata including subject matter classification, web page type, content complexity, and document quality scores for each of the 23.6 billion documents.
Researchers can filter and curate specialized datasets… See the full description on the dataset page: https://huggingface.co/datasets/EssentialAI/essential-web-v1.0.dclm-baseline-1.0-parquet
DCLM-baseline
Note: this is an identical copy of https://huggingface.co/datasets/mlfoundations/dclm-baseline-1.0, where all the files have been mapped to a parquet format.
DCLM-baseline is a 4T token / 3B document pretraining dataset that achieves strong performance on language model benchmarks.
Below are comparisions of model trained on DCLM-baseline with other models in the 7B regime.
Model
Params
Tokens
Open dataset?
CORE
MMLU
EXTENDED
Open weights, closed datasets… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations/dclm-baseline-1.0-parquet.droid_1.0.1This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "Franka",
"total_episodes": 95658,
"total_frames": 27630375,
"total_tasks": 49630,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 500,
"fps": 15,
"splits": {
"train": "0:95658"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/lerobot/droid_1.0.1.sdxl-1.0
check sdxl.parrotzone.art for easy viewing ⋆｡°✩
all images were made with SDXL 1.0 + the 0.9 VAE
steps: 20
cfg scale: 7
no refiner
random seeds