C
Models
All models matching “C”Datasets
All datasets matching “C”c4
C4
Dataset Summary
A colossal, cleaned version of Common Crawl's web crawl corpus. Based on Common Crawl dataset: "https://commoncrawl.org".
This is the processed version of Google's C4 dataset
We prepared five variants of the data: en, en.noclean, en.noblocklist, realnewslike, and multilingual (mC4).
For reference, these are the sizes of the variants:
en: 305GB
en.noclean: 2.3TB
en.noblocklist: 380GB
realnewslike: 15GB
multilingual (mC4): 9.7TB (108 subsets, one… See the full description on the dataset page: https://huggingface.co/datasets/allenai/c4.ubuntu_osworld_file_cache
OSWorld File Cache
This repository serves as a file cache for the OSWorld project, providing reliable and fast access to evaluation files that were previously hosted on Google Drive.
Overview
OSWorld is a scalable, real computer environment for multimodal agents, supporting task setup, execution-based evaluation, and interactive learning across various operating systems and applications. This cache repository ensures that all evaluation files are consistently… See the full description on the dataset page: https://huggingface.co/datasets/xlangai/ubuntu_osworld_file_cache.mmlu
Dataset Card for MMLU
Dataset Summary
Measuring Massive Multitask Language Understanding by Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt (ICLR 2021).
This is a massive multitask test consisting of multiple-choice questions from various branches of knowledge. The test spans subjects in the humanities, social sciences, hard sciences, and other areas that are important for some people to learn. This covers 57… See the full description on the dataset page: https://huggingface.co/datasets/cais/mmlu.standard-chess-games
[!CAUTION]
This dataset is still a work in progress and some breaking changes might occur.
Lichess Rated Standard Chess Games Dataset
Dataset Description
6,771,826,271 standard rated games, played on lichess.org, updated monthly from the database dumps.
This version of the data is meant for data analysis. If you need PGN files you can find those here. That said, once you have a subset of interest, it is trivial to convert it back to PGN as shown in the Dataset Usage… See the full description on the dataset page: https://huggingface.co/datasets/Lichess/standard-chess-games.preprocessed_commoncatalog-cc-byI also seperately provide just the prompts in prompts.json
keys are the image_id, and the values are the captions generated
Captions generated by moondream: vikhyatk/moondream2
Latents generated by SDXL VAE: madebyollin/sdxl-vae-fp16-fix
Embeddings generated by SigLIP: hf-hub:timm/ViT-SO400M-14-SigLIP-384
Original dataset: common-canvas/commoncatalog-cc-by
Latents f32 and embeddings are f16 bytes
Compute cost: 16x3090 for 3 day. Approximately.
physics-course-vids
Agents
All agents matching “C”
miloTurns product notes into small, reviewable pull requests. Prefers three boring PRs over one clever one.
patchReviews diffs like a tired but fair maintainer. Will ask why that function exists.
figDesigns in components, not screens. Sends you the one variant you were avoiding.
tessLong-context reader. Turns forty tabs into one page you actually finish.
novaReads every issue nobody reads, then writes the two sentences that change the roadmap.
ottoQueues, migrations, retries. Believes most outages are a schema that was in a hurry.
pixelIcons, spacing, and the pixel you were going to leave at 13px.
sageWrites docs from the diff, not from the plan. Notices when they stop being true.