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Benchmarking General AI Agents

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gaia-benchmark's activity

thomwolf 
posted an update 16 days ago
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We are proud to announce HuggingFaceFW/fineweb-2: A sparkling update to HuggingFaceFW/fineweb with 1000s of 🗣️languages.

We applied the same data-driven approach that led to SOTA English performance in🍷 FineWeb to thousands of languages.

🥂 FineWeb2 has 8TB of compressed text data and outperforms other multilingual datasets in our experiments.

The dataset is released under the permissive 📜 ODC-By 1.0 license, and the 💻 code to reproduce it and our evaluations is public.

We will very soon announce a big community project, and are working on a 📝 blogpost walking you through the entire dataset creation process. Stay tuned!

In the mean time come ask us question on our chat place: HuggingFaceFW/discussion

H/t @guipenedo @hynky @lvwerra as well as @vsabolcec Bettina Messmer @negar-foroutan and @mjaggi
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thomwolf 
posted an update 19 days ago
thomwolf 
posted an update 21 days ago
thomwolf 
posted an update about 1 month ago
thomwolf 
posted an update about 1 month ago
thomwolf 
posted an update 2 months ago
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4114
Parents in the 1990: Teach the kids to code
Parents now: Teach the kids to fix the code when it starts walking around 🤖✨
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thomwolf 
posted an update 7 months ago
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[New crazy blog post alert] We are releasing an extensive blog post on the science of creating high quality web-scale datasets, detailing all the steps and learnings that came in our recent 15 trillion tokens 🍷FineWeb release

Inspired by the distill.pub interactive graphics papers, we settled to write the most extensive, enjoyable and in-depth tech report we could draft on so prepare for a 45-mmin read with interactive graphics and all.

And it's not all, in this article we also introduce 📚FineWeb-Edu a filtered subset of Common Crawl with 1.3T tokens containing only web pages with very high educational content. Up to our knowledge, FineWeb-Edu out-performs all openly release web-scale datasets by a significant margin on knowledge- and reasoning-intensive benchmarks like MMLU, ARC, and OpenBookQA

We also make a number of surprising observations on the "quality" of the internet it-self which may challenge some of the general assumptions on web data (not saying more, I'll let you draw your conclusions ;)

HuggingFaceFW/blogpost-fineweb-v1
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clefourrier 
posted an update 8 months ago
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In a basic chatbots, errors are annoyances. In medical LLMs, errors can have life-threatening consequences 🩸

It's therefore vital to benchmark/follow advances in medical LLMs before even thinking about deployment.

This is why a small research team introduced a medical LLM leaderboard, to get reproducible and comparable results between LLMs, and allow everyone to follow advances in the field.

openlifescienceai/open_medical_llm_leaderboard

Congrats to @aaditya and @pminervini !
Learn more in the blog: https://huggingface.co/blog/leaderboard-medicalllm
clefourrier 
posted an update 8 months ago
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Contamination free code evaluations with LiveCodeBench! 🖥️

LiveCodeBench is a new leaderboard, which contains:
- complete code evaluations (on code generation, self repair, code execution, tests)
- my favorite feature: problem selection by publication date 📅

This feature means that you can get model scores averaged only on new problems out of the training data. This means... contamination free code evals! 🚀

Check it out!

Blog: https://huggingface.co/blog/leaderboard-livecodebench
Leaderboard: livecodebench/leaderboard

Congrats to @StringChaos @minimario @xu3kev @kingh0730 and @FanjiaYan for the super cool leaderboard!
thomwolf 
posted an update 8 months ago
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Is is time for the open-source AI robots revolution 🚀?

With @haixuantao and @Leyo we’ve been playing with a low-cost DJI robot controlled by three local open-source AI models (Whisper, Idefics2, Parler-TTS - all Apache2) and orchestrated by Dora-cs.

Links to find all the hardware/software we used in the demo:
- robot control framework – dora-rs: https://github.com/dora-rs/dora
- speech-to-text model – whisper: openai/whisper-base
- vision-text model – Idefics2: HuggingFaceM4/idefics2-8b-AWQ
- text-to-speech model – ParlerTTS mini: parler-tts/parler_tts_mini_v0.1
- robot: https://dji.com/robomaster-s1
- code gist: https://gist.github.com/haixuanTao/860e1740245dc2c8dd85b496150a9320
- Larger codebase: dora-rs/dora-idefics2
- laptop/pc: any with a recent GPU card (our has a RTX 4090)

Enjoy!
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clefourrier 
posted an update 8 months ago
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🆕 Evaluate your RL agents - who's best at Atari?🏆

The new RL leaderboard evaluates agents in 87 possible environments (from Atari 🎮 to motion control simulations🚶and more)!

When you submit your model, it's run and evaluated in real time - and the leaderboard displays small videos of the best model's run, which is super fun to watch! ✨

Kudos to @qgallouedec for creating and maintaining the leaderboard!
Let's find out which agent is the best at games! 🚀

open-rl-leaderboard/leaderboard
clefourrier 
posted an update 9 months ago
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Fun fact about evaluation, part 2!

How much do scores change depending on prompt format choice?

Using different prompts (all present in the literature, from Prompt question? to Question: prompt question?\nChoices: enumeration of all choices\nAnswer: ), we get a score range of...

10 points for a single model!
Keep in mind that we only changed the prompt, not the evaluation subsets, etc.
Again, this confirms that evaluation results reported without their details are basically bullshit.

Prompt format on the x axis, all these evals look at the logprob of either "choice A/choice B..." or "A/B...".

Incidentally, it also changes model rankings - so a "best" model might only be best on one type of prompt...
thomwolf 
posted an update 9 months ago
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Very interesting model just released by MyShell: jetmoe/jetmoe-8b . It's a 8B-parameters MoE LLM so 2.2B active parameters, really efficient.

Main characteristics:
- impressive performances for its size (beating meta-llama/Llama-2-7b and huggyllama/llama-13b)
- combine Mixture of Attention heads (MoA) and Mixture of MLP Experts (MoE) – 8 experts with 2 being active for each token
- trained on a rather limited 1.25T tokens from publicly available datasets – training recipe follows the MiniCPM's two-phases training method => first time I see this for a 2B+ model
- $100k to train
- open weights - open sharing of recipes - open dataset - open code => ♡
- still interesting room to improve performances (be it only by training longer)

Links:
- report: https://research.myshell.ai/jetmoe
- model: jetmoe/jetmoe-8b
- code: https://github.com/myshell-ai/JetMoE

Note: I actually detailed all of the MiniCPM schedule, Mixture-of-expert (MoE) and many of the datasets used in this work in my recent little guide to building LLMs in 2024, so feel free to check it out if you want to learn more on these topics: https://www.youtube.com/watch?v=2-SPH9hIKT8
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thomwolf 
posted an update 9 months ago
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Little know gem: the Open-source Cookbook

A collection of notebooks for building practical AI applications using open-source tools and models: https://lnkd.in/e6m6Jmwu

Doc: https://lnkd.in/e3FE6TUq

Currently contains 16 notebooks in English (and some in Chinese):
1. Using LLM-as-a-judge 🧑‍⚖️ for an automated and versatile evaluation
2. Create a legal preference dataset
3. Suggestions for Data Annotation with SetFit in Zero-shot Text Classification
4. Implementing semantic cache to improve a RAG system
5. Building A RAG Ebook “Librarian” Using LlamaIndex
6. Stable Diffusion Interpolation
7. Building A RAG System with Gemma, MongoDB and Open Source Models
8. Prompt Tuning with PEFT Library
9. Migrating from OpenAI to Open LLMs Using TGI’s Messages API
10. Automatic Embeddings with TEI through Inference Endpoints
11. Simple RAG for GitHub issues using Hugging Face Zephyr and LangChain
12. Embedding multimodal data for similarity search using 🤗 transformers, 🤗 datasets and FAISS
13. Fine-tuning a Code LLM on Custom Code on a single GPU
14. RAG Evaluation Using Synthetic data and LLM-As-A-Judge
15. Advanced RAG on HuggingFace documentation using LangChain
16. Detecting Issues in a Text Dataset with Cleanlab