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liked a model 34 minutes ago
meta-llama/Llama-4-Scout-17B-16E-Instruct
liked a model 34 minutes ago
meta-llama/Llama-4-Maverick-17B-128E-Instruct
reacted to merterbak's post with 🔥 about 1 hour ago
Meta has unveiled its Llama 4 🦙 family of models, featuring native multimodality and mixture-of-experts architecture. Two model families are available now: Models🤗: https://huggingface.co/collections/meta-llama/llama-4-67f0c30d9fe03840bc9d0164 Blog Post: https://ai.meta.com/blog/llama-4-multimodal-intelligence/ HF's Blog Post: https://huggingface.co/blog/llama4-release - 🧠 Native Multimodality - Process text and images in a unified architecture - 🔍 Mixture-of-Experts - First Llama models using MoE for incredible efficiency - 📏 Super Long Context - Up to 10M tokens - 🌐 Multilingual Power - Trained on 200 languages with 10x more multilingual tokens than Llama 3 (including over 100 languages with over 1 billion tokens each) 🔹 Llama 4 Scout - 17B active parameters (109B total) - 16 experts architecture - 10M context window - Fits on a single H100 GPU - Beats Gemma 3, Gemini 2.0 Flash-Lite, and Mistral 3.1 🔹 Llama 4 Maverick - 17B active parameters (400B total) - 128 experts architecture - It can fit perfectly on DGX H100(8x H100) - 1M context window - Outperforms GPT-4o and Gemini 2.0 Flash - ELO score of 1417 on LMArena currently second best model on arena 🔹 Llama 4 Behemoth (Coming Soon) - 288B active parameters (2T total) - 16 experts architecture - Teacher model for Scout and Maverick - Outperforms GPT-4.5, Claude Sonnet 3.7, and Gemini 2.0 Pro on STEM benchmarks
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upvoted a collection about 1 hour ago
upvoted an article 11 days ago
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XetHub is joining Hugging Face!

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upvoted 2 articles about 2 months ago
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From Chunks to Blocks: Accelerating Uploads and Downloads on the Hub

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Open-R1: a fully open reproduction of DeepSeek-R1

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upvoted a paper 9 months ago