Research Scientist @Meta Superintelligence Labs. ex-@GoogleDeepMind - Gemma. PhD @IP_Paris_ | @Mila_Quebec | MSc MVA | @ENS_ULM
Paris
Joined October 2015
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Thomas Mesnard retweeted
Muse Spark Open -- weights releasing today -- runs great on new Mac Studios thanks to work with @johnternus and Apple.
Thomas Mesnard retweeted
MUSE WONDER
this is the culmination of over a year of research and infrastructure work in msl
since we originally shipped muse spark in april, we have continued to scale our models across pre-training and RL, now reaching the frontier 🏆
see our model's improvements on the artificial analysis index:
Thomas Mesnard retweeted
Excited to share what we have been cooking in the past few months: Muse Glimmer: research.meta.ai/blog/introd…
Thomas Mesnard retweeted
Introducing Muse Glimmer, an open-weight 30B-parameter model optimized for local, always-on agent workflows.
Muse Glimmer delivers strong performance on key agentic use cases and benchmarks compared with leading models in its size category, and is designed to run entirely on consumer hardware like a Mac or PCs with performant GPUs.
In keeping with our long tradition of sharing fundamental AI research, we’re releasing model weights under a permissive Apache 2.0 license.
🧵👇
Thomas Mesnard retweeted
1/ today we're releasing muse spark, the first model from MSL. nine months ago we rebuilt our ai stack from scratch. new infrastructure, new architecture, new data pipelines. muse spark is the result of that work, and now it powers meta ai. 🧵
Thomas Mesnard retweeted
An exciting milestone for AI in science: Our C2S-Scale 27B foundation model, built with @Yale and based on Gemma, generated a novel hypothesis about cancer cellular behavior, which scientists experimentally validated in living cells.
With more preclinical and clinical tests, this discovery may reveal a promising new pathway for developing therapies to fight cancer.
Thomas Mesnard retweeted
Introducing EmbeddingGemma, our newest open model that can run completely on-device. It's the top model under 500M parameters on the MTEB benchmark and comparable to models nearly 2x its size – enabling state-of-the-art embeddings for search, retrieval + more.
Thomas Mesnard retweeted
Introducing EmbeddingGemma🎉
🔥With only 308M params, this is the top open model under 500M
🌏Trained on 100+ languages
🪆Flexible embeddings (768 to 128 dims) with Matryoshka
🤗Works with your favorite open tools
🤏Runs with as little as 200MB
developers.googleblog.com/en…
Thomas Mesnard retweeted
We've had a busy August!
August at Google DeepMind was like 🧞♂️ 🖼️ 🍌 🚀 🔍 🤏🏻
- Nano Banana (Gemini 2.5 Flash Image)
- Gemini Embedding
- Veo 3 Fast
- Genie 3
- Imagen 4 Fast
- Gemma 3 270M
- Perch 2
- Kaggle Game Arena
- Gemini API Url Context
- AI Studio Builder (UI Rework, Prompt Suggestions, GitHub integration …)
- AI studio UI (Model Picker, Chat, Scrolling…)
and much more!
Thomas Mesnard retweeted
Looking for a small or medium sized VLM? PaliGemma 2 spans more than 150x of compute!
Not sure yet if you want to invest the time 🪄finetuning🪄 on your data? Give it a try with our ready-to-use "mix" checkpoints:
🤗 huggingface.co/blog/paligemm…
🎤 developers.googleblog.com/en…
Thomas Mesnard retweeted
Thrilled to launch the PaliGemma 2 Mix models today! Try out class-leading vision-language models from 3B to 28B =). #gemmaverse
PaliGemma 2 mix is an upgraded vision-language model that supports image captioning, OCR, image Q&A, object detection, and segmentation. With sizes from 3B-28B parameters, there's a model for everyone. Get started. → goo.gle/430HnDe
ALT The text "PaliGemma 2 mix" is centered on a dark background with smaller images and text snippets surrounding it, showcasing examples of image captioning and location identification.
Thomas Mesnard retweeted
🚀🚀PaliGemma 2 is our updated and improved PaliGemma release using the Gemma 2 models and providing new pre-trained checkpoints for the full cross product of {224px,448px,896px} resolutions and {3B,10B,28B} model sizes.
1/7
Thomas Mesnard retweeted
Thrilled to announce the launch of PaliGemma 2, a state-of-the-art update to our PaliGemma vision-language models! These models are based on Gemma 2, and are available today in 2B, 9B, and 27B sizes.
developers.googleblog.com/en…
huggingface.co/blog/paligemm…
Thomas Mesnard retweeted
📢 Exciting opportunity alert!
We (valeo.ai) just posted our annual research internship openings in computer vision & ML.
Check out the openings and the great achievements by our past interns here: valeoai.github.io/interns/
🌟 Calling all MSc students passionate about computer vision and ML!
We’re offering research internships about diffusion models, multi-modal transformers, continual learning, & more. 4 exciting openings await!
🔗 Learn more: valeoai.github.io/interns/
RT to spread the word! 🙌
Thomas Mesnard retweeted
Gemma 2 just got even better! 🚀 New Japanese-tuned 2B model AND a $150K Kaggle competition to build Gemma models for every language. Great to have @sundarpichai here to share the excitement!
Read more: goo.gle/Gemma4Japan
#GemmaDeveloperDay
Thomas Mesnard retweeted
Princeton's Gemma 2 9B SimPO fine-tuned model is doing amazing on @lmsysorg 🤯📈
You can find it on @huggingface : huggingface.co/princeton-nlp…
Nice work @yumeng0818 @xiamengzhou & @danqi_chen
ALT Screenshot of the LMSys leaderboard with Princeton's 9B Gemma model tied with Gemma 27B
Thomas Mesnard retweeted
Imagine a 27B LLM can beat a 405B model in writing quality code by investing a few milliseconds in static code repair. Now stop imagining and take a look at this chart 🌈
Just for Go, we have the following stats:
- Increases score +22.9% across 45 applicable models
- +26.2% response files compiled (avg. 17 files, 150 tasks total)
- mistral-tiny has +71% in score: beats mistral-small and mistral-medium
- Gemma 2 27B has +16% in score: beats GPT4o and Llama 3.1 405B
Proof that the approach of doing code fixes over a static analysis should be the default for every code response and coding assistant. Makes code instantly more useful.
Thomas Mesnard retweeted
Gemma 2 2B running in a browser, powered by WebLLM & WebGPU! 🔥
100% local & on-device
In less than 24 hours, we've already got the model to the edge! ⚡
Try it out on an HF space below:
Thomas Mesnard retweeted
Quantized Gemma 2B runs pretty fast on my iPhone 15 pro in MLX Swift.
code & docs: github.com/ml-explore/mlx-sw…
Comparable to GPT 3.5 turbo and Mixtral 8x7B in
@lmsysorg benchmarks but runs efficiently on an iPhone. Pretty wild.