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salma-remyx
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reacted to AC-723's post with 🔥 3 days ago
MixtureKit 1.1 is out 🚀 Turn the fine-tuned models you already have on the Hub into one Mixture-of-Experts model. pip install mixturekit Give it a base model and its fine-tunes (math, code, a language...). MixtureKit merges them, trains the routers that pick an expert for every token, and shows you what they learned: 🧩 3 composition methods behind one YAML: Branch-Train-MiX, Mixtral-style MoE, Branch-Train-Stitch 💻 Merges stream the experts tensor by tensor: they run on a laptop 🎯 Router training with a load balancing loss, optional LoRA 🔍 A routing visualizer: in the image, two Nile 4B experts split a mixed Egyptian sentence, Arabic script to one expert, Arabizi to the other 📦 Export to Mixtral / Qwen3-MoE, then GGUF for llama.cpp 🤗 mixturekit push uploads the result with a generated model card ✅ Llama 3, Qwen 2.5/3/3.5, Gemma 3/4 experts; tested on transformers 4.52 to 5.19 In the paper, a BTX model built with MixtureKit outperforms the dense baselines on multiple benchmarks. ▶️ Build, train and visualize an MoE in 15 min on a free Colab GPU: https://colab.research.google.com/github/MBZUAI-Paris/MixtureKit/blob/main/examples/build_your_own_moe.ipynb 📄 Paper: https://huggingface.co/papers/2512.12121 💻 Code: https://github.com/MBZUAI-Paris/MixtureKit 📚 Docs: https://mbzuai-paris.github.io/MixtureKit/ Work with @guokan-shang and @oe2015 at @MBZUAI-Paris 🙌
reacted to Jiaqi-hkust's post with 🔥 3 days ago
We open-sourced Game-Creation-Agents — an agentic system that turns a one-line game idea into a playable browser game. 🎮 Why it matters: - It lowers the barrier: you don’t need a full studio or deep engine skills to start. - It compresses prototyping from weeks to hours. - It lets creators test more ideas, faster, and focus on what’s actually fun. - It brings game creation closer to a conversation — and makes it accessible to more people. This isn’t just about generating code. It’s about giving more people the power to bring their ideas to life. Try it: https://github.com/Tencent/Game-Creation-Agents #AI #GameDev #OpenSource
reacted to Gjusev's post with 🔥 5 days ago
I retracted my own launch claim in public commits, then shipped what survived. MK-SH-1 is a 140M decision model I built on an open encoder. It returns calibrated probabilities, a choice, and an explicit abstention below a frozen gate (tau = 0.79, written down before the curve existed). ECE 0.016 · 90% coverage in-sample; held-out numbers in the card · 106 ms on CPU. https://huggingface.co/Gjusev/MK-SH-1 Demo https://huggingface.co/spaces/Gjusev/MK-SH-1-demo Full record, retraction included https://github.com/Gjusev/MK-SH-1
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