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We’re releasing model weights for our 8B- parameter Dynamic Byte Latent Transformer, an alternative to traditional tokenization methods with the potential to redefine the standards for language model efficiency and reliability. Learn more about how Dynamic Byte Latent Transformer is paving the way for groundbreaking developments in the field...

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AI at Meta

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195,705 просмотров • 1 год назад •via X (Twitter)

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4/ to achieve maximum memory efficiency, we quantize model weights to ~4-bit, getting the language model under 20GB with room for the kv cache, perception encoder, and drafter alongside it. a dflash drafter proposes blocks of tokens the main model verifies in parallel, so it stays responsive.
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4/ to achieve maximum memory efficiency, we quantize model weights to ~4-bit, getting the language model under 20GB with room for the kv cache, perception encoder, and drafter alongside it. a dflash drafter proposes blocks of tokens the main model verifies in parallel, so it stays responsive.

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🚨 We're very happy to introduce TRIBE v2: a foundation model of the brain's responses to sight, sound & language. 📄 Paper: ▶️ Demo: 💻 Code: 🤗 Model:

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Your gaming gpu might be capable of more than you think 💀 NSFW Wan 1.3B is a community model for uncensored text-to-video generation, now available on Hugging Face. → 2.8GB model file → around 8GB VRAM for the base model → 480p video generation → runs locally through ComfyUI how to try it :) visit the Hugging Face model page download wan_1.3B_exp_e14 set up ComfyUI with the Wan 2.1 workflow load the model and test it locally model link: 18+ only. Check the model license and requirements before downloading.

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We are excited to launch our two models Pharia-1-LLM-7B-control and Pharia-1-LLM-7B-control-aligned. Both models and the code used to train them are now publicly available and open-sourced for non-commercial research and educational use. Read our model blog post here: Learn more about our open-source codebase Scaling: #writtenbyalephalpha

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