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AI 模型 85003

• nomic-ai_-_gpt4all-falcon-gguf↗

  RichardErkhov

• distilbert-base-multilingual-cased-Sent_Negativo_Esp↗

  rogelioplatt

• Qwen2.5-14B-Roleplay-GGUF↗

  Ruandrew1234

• ornith-1.5-9b-ninfer↗

  ruwwww

• TinySwallow-1.5B-Instruct-GGUF↗

  SakanaAI

• Sequential-Hidden-Decoding-8B-n8↗

  腾讯

• clip-vit-base-patch32_oxford_flowers102↗

  tanganke

• d38a11↗

  tao1000

• vit_base_patch16_224.augreg_in21k_ft_in1k↗

  timm

  A Vision Transformer (ViT) image classification model. Trained on ImageNet-21k and fine-tuned on ImageNet-1k (with additional augmentation and regularization) in JAX by paper authors, ported to PyTorch by Ross Wightman. - **Model Type:** Image classification / feature backbone - **Model Stats:** - Params (M): 86.6 - GMACs: 16.9 - Activations (M): 16.5 - Image size: 224 x 224 - **Papers:** - How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers: https://arxiv.org/abs/2106.10270 - An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale: https://arxiv.org/abs/2010.11929v2 - **Dataset:** ImageNet-1k - **Pretrain Dataset:** ImageNet-21k - **Original:** https://github.com/google-research/vision_transformer Explore the dataset and runtime metrics of this model in timm model results.

• xception41p.ra3_in1k↗

  timm