facebook/MoEViE-L16-384开源了新模型

facebook/MoEViE-L16-384 · Hugging Face Hugging Face (https://huggingface.co/) Models (https://huggingface.co/models) Datasets (https://huggingface.co/datasets) Spaces (https://huggingface.co/spaces) Buckets new (https://huggingface.co/storage) Docs (https://huggingface.co/docs) Enterprise (https://huggingface.co/enterprise) Pricing (https://huggingface.co/pricing) Website Tasks (https://huggingface.co/tasks) HuggingChat (https://huggingface.co/chat) Collections (https://huggingface.co/collections) Languages (https://huggingface.co/languages) Organizations (https://huggingface.co/organizations) Community Blog (https://huggingface.co/blog) Posts (https://huggingface.co/posts) Daily Papers (https://huggingface.co/papers) Hardware (https://huggingface.co/hardware) Learn (https://huggingface.co/learn) Discord (https://huggingface.co/join/discord) Forum (https://discuss.huggingface.co/) GitHub (https://github.com/huggingface) Solutions Team & Enterprise (https://huggingface.co/enterprise) Hugging Face PRO (https://huggingface.co/pro) Enterprise Support (https://huggingface.co/support) Inference Providers (https://huggingface.co/inference/models) Inference Endpoints (https://huggingface.co/inference-endpoints) Storage Buckets (https://huggingface.co/storage) Log In (https://huggingface.co/login) Sign Up (https://huggingface.co/join) (https://huggingface.co/facebook) facebook (https://huggingface.co/facebook) / MoEViE-L16-384 (https://huggingface.co/facebook/MoEViE-L16-384) like 2 Follow AI at Meta 14.1k Zero-Shot Image Classification (https://huggingface.co/models?pipeline_tag=zero-shot-image-classification) moe_vie (https://huggingface.co/models?other=moe_vie) arxiv: 2608.17402 License: cc-by-nc-4.0 Model card (https://huggingface.co/facebook/MoEViE-L16-384) Files Files and versions xet (https://huggingface.co/facebook/MoEViE-L16-384/tree/main) Community (https://huggingface.co/facebook/MoEViE-L16-384/discussions) Copy to bucket new Model Details (https://huggingface.co/facebook/MoEViE-L16-384#model-details) Model Configurations (https://huggingface.co/facebook/MoEViE-L16-384#model-configurations) Model Performance (https://huggingface.co/facebook/MoEViE-L16-384#model-performance) How to use (https://huggingface.co/facebook/MoEViE-L16-384#how-to-use) Install (https://huggingface.co/facebook/MoEViE-L16-384#install) Image and text feature extraction (https://huggingface.co/facebook/MoEViE-L16-384#image-and-text-feature-extraction) License (https://huggingface.co/facebook/MoEViE-L16-384#license) Citation (https://huggingface.co/facebook/MoEViE-L16-384#citation) (https://huggingface.co/facebook/MoEViE-L16-384#model-details) Model Details [📃 Paper] (https://arxiv.org/abs/2608.17402) [📂 GitHub] (https://github.com/facebookresearch/moe_vie) MoE-ViE is a family of Mixture-of-Experts vision encoders for image and video understanding, trained with a contrastive vision-language recipe. Each MoE block keeps a shared always-on expert alongside a routed pool, so only a small fraction of the weights is used for any given token. Model Developer: Meta This checkpoint: MoEViE-L16-384 — L/16 at 384px. (https://huggingface.co/facebook/MoEViE-L16-384#model-configurations) Model Configurations MoE-ViE comes in three sizes. Only active experts run per token, so the activated parameter count is far below the total. Scale Width Depth Experts (active/total) Total params Activated params Resolution B/16 768 12 4 / 32 0.5B 0.1B 224px L/16 1024 24 4 / 32 1.7B 0.3B 384px H/14 1280 32 8 / 32 3.5B 1.1B 448px Every MoE block has 1 shared expert that is always active plus a routed pool; the active/total column counts the shared expert. Routing is per-token top-k on a sigmoid gate. (https://huggingface.co/facebook/MoEViE-L16-384#model-performance) Model Performance Zero-shot results. Top-1 accuracy (%) for classification, recall@1 (%) for retrieval. Model Checkpoint IN-1k ObjectNet COCO-T2I Kinetics-400 MSR-VTT-T2V

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