Right now, single-turn tasks only, but I will very likely expand this to multi-turn generation soon!
CODE
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Codestral 25.08 and Complete Mistral Coding Stack Launch
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Meet the new Codestral 25.08 and the Complete Mistral Coding Stack for Enterprises!
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Vibe Training Replaces Vibe Coding in AI Development
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Forget vibe coding. Vibe *training* is now a thing.
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Early LSTM Language Model Architecture Recognition from NLP Community
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Special thanks to the NLP community for the recognition. This was my earliest work in "large" language model at the time , quoted from the paper "Our stacking LSTM models have 4 layers, each with 1000 cells, and 1000-dimensional embeddings" .
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AutoRL: Train AI Models for Any Task via GitHub
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If you'd like to try it or contribute, check out the Github repo and notebook: https://
github.com/OpenPipe/ART/t
ree/auto-rl?tab=readme-ov-file#-autorl-train-models-for-any-task
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OpenPipe’s RULER Enables LLM Training Without Labeled Data
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Under the hood, this is powered by @OpenPipeAI
's ART library. Their RULER technique made this possible, as it doesn't require labeled output data. With no need for labeled outputs, we can just sample a LLM to generate scenarios to RL against. Absolutely crazy! -
Fast AI Model Training System Delivers Impressive Grammar Results
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It's incredible how quickly you can go from an idea to a fully-trained model with this system. And the resulting models are really good! The grammar model in the demo video works really well, yet it was trained for just minutes, and was only 1.5B params 🙂
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AutoRL: Simplest Way to Train Task-Specific LLMs
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Introducing `AutoRL` 📈
— Matt Shumer (@mattshumer_) 30 juillet 2025
The world's simplest way to train a task-specific LLM with RL.
*Just write a SENTENCE describing the model you want.*
A chain of AI systems will generate data + rubrics and train a model for you.
Powered by ART, it's open source.
Link in thread: pic.twitter.com/OVxe2hWTZYIntroducing `AutoRL` The world's simplest way to train a task-specific LLM with RL. *Just write a SENTENCE describing the model you want.* A chain of AI systems will generate data + rubrics and train a model for you. Powered by ART, it's open source. Link in thread:
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AutoRL: Automated Reinforcement Learning for Model Generation
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How AutoRL works, in a nutshell: – The user describes the model they want
Ex: "A model that detects spelling and grammar errors" – OSS models generate a system prompt that will be used a) to generate, and b) for RULER to rank outputs – We generate input data, and RL a model!