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AI 模型 84759

• Quill-v1-imatrix-GGUF↗

  duyntnet

• eagle-deepseek-v3-random↗

  eagle618

• resnet50_cifar10↗

  edadaltocg

• MobileLLM-ParetoQ-1B-1-bit↗

  facebook

• sapiens2-pretrain-0.8b↗

  facebook

• FastVideo-FastH3-4-step-Preview-v1-LoRA↗

  FastVideo

  The compact LoRA releases for FastH3 Preview v1 from FastVideo. Each adapter reconstructs one four-forward FastH3 transformer from the MiniMax H3 base model. > The three VSA adapters require FastVideo's VSA-H3 backend and kernel. Use > FastVideo's launchers rather than a generic PEFT loader; these adapters also > contain exact delta and VSA gate tensors. Install uv, then use the CUDA 13 / Blackwell path below. It selects FastVideo's published CUDA kernel wheel instead of compiling the kernel locally. See the installation guide for other platforms.

• nor-100mb-after-wc-loglinear-newlex-before-ckpt500-packed-bfdiso_seed455↗

  francesca9805

• t2sql-gguf↗

  gguf-org

• Josiefied-Qwen2.5-1.5B-Instruct-abliterated-v1↗

  Goekdeniz-Guelmez

• byt5-small↗

  Google

  ByT5 is a tokenizer-free version of Google's T5 and generally follows the architecture of MT5. ByT5 was only pre-trained on mC4 excluding any supervised training with an average span-mask of 20 UTF-8 characters. Therefore, this model has to be fine-tuned before it is useable on a downstream task. ByT5 works especially well on noisy text data,*e.g.*, `google/byt5-small` significantly outperforms mt5-small on TweetQA.