Elie

@eliebak.hf.co

Training LLM's at huggingface | hf.co/science

LLM Reasoning labs will be eating good today🍔 We commandeered the HF cluster for a few days and generated 1.2M reasoning-filled solutions to 500k NuminaMath problems with DeepSeek-R1 🐳 Have fun!

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Introducing 📐FineMath: the best open math pre-training dataset with 50B+ tokens! Math remains challenging for LLMs and by training on FineMath we see considerable gains over other math datasets, especially on GSM8K and MATH. 🤗 huggingface.co/datasets/Hug... Here’s a breakdown 🧵

A plot showing increased performance of Llama-3.2-3B when pretrained on FineMath

WOW, Gemini Flash 2.0 is really impressive. Wondering about the size of this supposedly smol model. One odd thing is that the model seems to lose some ability with long contexts compared to Flash 1.5. If any google friends could share insights, I'd love to hear them!

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Hey, I'll be at neurips next week! My DM are open if you want to meet and talk about pre-training/data/whatever you want 🫡

Google patent on "Training of large neural network". 😮 I don't know if this give much information but by going quickly through it seems that: - They are not only using "causal language modeling task" as a pre-training task but also "span corruption" and "prefix modeling". (ref [0805]-[0091])

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What else should we log during LLM training? Right now, it's just loss, grad_norm, and evals, but I want to log more to have a better understanding of pre-training. Thinking about adding stuff like entropix metrics (agreement, varentropy?) Any thoughts or cool ideas?

WOW! 🤯 Language models are becoming smaller and more capable than ever! Here's SmolLM2 running 100% locally in-browser w/ WebGPU on a 6-year-old GPU. Just look at that speed! ⚡️😍 Powered by 🤗 Transformers.js and ONNX Runtime Web! How many tokens/second do you get? Let me know! 👇

I'm looking for an intern! If you are: * Driven * Love OSS * Interested in distributed PyTorch training/FSDPv2/DeepSpeed Come work with me! Fully remote, more details to apply in the comments

A job description stating:
About this Role

This internship works at the intersections of software engineering, machine learning engineering, and education. With a strong focus on distributed training through the accelerate library (https://huggingface.co/docs/accelerate/index), we'll focus on bringing state-of-the-art training techniques into the library while also documenting and helping
teach others how they work. By the end of this internship, the candidate will have touched on all aspects of distributed training and core library contributions, including large-scale distributed training, API design, writing educational material aimed at a semi-technical audience, and
understanding the nuances of writing software that scales.

On the Xet team at @huggingface.bsky.social we're always looking for ways to move bytes to computer near you as fast as possible. To do this, we're redesigning the upload and download infrastructure on the Hub. This post describes how, check the thread for details 🧵 huggingface.co/blog/rearchi...

Rearchitecting Hugging Face Uploads and Downloads

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

huggingface.co

The SmolLM series has a new member: say hi to SmolVLM! 🤏 It uses a preliminary 16k context version of SmolLM2 to tackle long-context vision documents and higher-res images. And yes, we’re cooking up versions with bigger context lengths. 👨‍🍳 Try it yourself here: huggingface.co/spaces/Huggi...

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Small yet mighty! 💫 We are releasing SmolVLM: a new 2B small vision language made for on-device use, fine-tunable on consumer GPU, immensely memory efficient 🤠 We release three checkpoints under Apache 2.0: SmolVLM-Instruct, SmolVLM-Synthetic and SmolVLM-Base huggingface.co/collections/...

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Let's go! We are releasing SmolVLM, a smol 2B VLM built for on-device inference that outperforms all models at similar GPU RAM usage and tokens throughputs. SmolVLM can be fine-tuned on a Google collab and be run on a laptop! Or process millions of documents with a consumer GPU!

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Check out how easy it is to do LLM evals with LightEval! * any dataset on the 🤗 Hub can become an eval task in a few lines of code: customize the prompt, metrics, parsing, few-shots, everything! * model- and data-parallel inference * auto batching with the new vLLM backend

A screenshot of LightEval benchmarking results in a terminal

Hey babe, wake up, we just dropped a new SmolLM 🫡 Fully open-source. We’ll release a blog post soon to detail how we trained it. I'm also super excited about all the demos that will come in the next few days, especially looking forward for people to test it with entropix 🐸

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Since there is all this AI migration on Bluesky: my sister @pandorai1995.bsky.social is looking for an experience in VLM/LLM. She just wrote an amazing in-depth report on OCR by VLMs like Qwen/Florence on @huggingface.bsky.social [Repost appreciated]

Alexander Doria@dorialexander.bsky.social · 2y ago

Are Visual Language Models a game changer for OCR and the transcription of challenging texts? @pandorai1995.bsky.social just published a lengthy report on @huggingface.bsky.social with one main catch: it's complicated. huggingface.co/blog/PandorA...