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AI 模型 84760

• Pony-Realism-GGUF↗

  nuupy

• mit-b4↗

  NVIDIA

  SegFormer encoder fine-tuned on Imagenet-1k. It was introduced in the paper SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers by Xie et al. and first released in this repository. Disclaimer: The team releasing SegFormer did not write a model card for this model so this model card has been written by the Hugging Face team. SegFormer consists of a hierarchical Transformer encoder and a lightweight all-MLP decode head to achieve great results on semantic segmentation benchmarks such as ADE20K and Cityscapes. The hierarchical Transformer is first pre-trained on ImageNet-1k, after which a decode head is added and fine-tuned altogether on a downstream dataset.

• Qwen2.5-VL-7B-Surg-CholecT50↗

  NVIDIA

• Supertonic-TTS-ONNX↗

  onnx-community

• Flint-40B-A2.5B-JANG_4M↗

  OsaurusAI

• herbert-base-ner↗

  pczarnik

  **herbert-base-ner** is a fine-tuned HerBERT model that can be used for **Named Entity Recognition** . It has been trained to recognize three types of entities: person (PER), location (LOC) and organization (ORG). Specifically, this model is an *allegro/herbert-base-cased* model that was fine-tuned on the Polish subset of *wikiann* dataset.

• Qwen-Image-2.1-PE-T2I-MLX↗

  prithivMLmods

• corticalclock↗

  pyaging

• DETR-ResNet101↗

  qualcomm

• Mistral-Nemo-12B-ArliAI-RPMax-v1.2-GGUF↗

  QuantFactory