Welcome to open-source world models! https://t.co/IXVxZdGm4r
— clem 🤗 (@ClementDelangue) 12 août 2025
Welcome to open-source world models!
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Welcome to open-source world models! https://t.co/IXVxZdGm4r
— clem 🤗 (@ClementDelangue) 12 août 2025
Welcome to open-source world models!
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Jan-v1 4B model for web search, an open-source alternative to Perplexity Pro?
— Chubby♨️ (@kimmonismus) 12 août 2025
Yes, please! Really cool! https://t.co/VBGhcxwqvs
Jan-v1 4B model for web search, an open-source alternative to Perplexity Pro? Yes, please! Really cool!

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new blog! i got mad at openai and vibe-coded a triton kernel

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figured out how to "undo" the RL and turn gpt-oss back into a base model will drop the weights tomorrow gn
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torchtitan has an MoE impl that supports grouped mm and composes with FSDP: https://
github.com/pytorch/torcht
itan/blob/main/torchtitan/models/moe.py
… needs the latest torch version though (2.8) which flash-attn doesnt have a wheel for yet 🙁
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Stay tuned for more such interesting posts → @Saboo_Shubham_ I have created 100+ AI Agents and RAG tutorials, 100% free and opensource. P.S: Don't forget to star the repo to show your support

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LangChain literally reverse-engineered Claude Code and Manus AI to build Deep Agents. It's a Python library to turn any LLM into a deep thinking agent with MCP tools. 100% opensource.
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LangExtract = Google's Python library for extracting structured information from unstructured text using LLMs:
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It's pretty easy with torchrun, fsdp, etc.
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🚀 New Breakthrough in Vision-Language Reasoning 🧠🖼️
— Dr. Debashis Dutta (@debashis_dutta) 12 août 2025
Originally shared by @WenhuChen — Pixel Reasoner is the first open-source framework enabling Vision-Language Models (VLMs) to “think in pixel space” through curiosity-driven reinforcement learning.
💡 The Challenge
Most… pic.twitter.com/IXCFVuNMeM
New Breakthrough in Vision-Language Reasoning Originally shared by @WenhuChen — Pixel Reasoner is the first open-source framework enabling Vision-Language Models (VLMs) to “think in pixel space” through curiosity-driven reinforcement learning. The Challenge Most