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AI モデル 84759
- Loom-Spark-3.2↗
textilelabs
- Llama2-22B-Daydreamer-v3-GGUF↗
TheBloke
- gemma-4-26B-A4B-it-uncensored-heretic-ara-MLX-8bit-int8-affine-betterCache↗
TheDrewBenson
- Qwen3.6-27B-Fable-Fusion-711-Uncensored-Heretic-NM-DAU-NEO-MAX-MTP-GGUF↗
TheMasterBlahBlah
- maxvit_tiny_tf_224.in1k↗
timm
An official MaxViT image classification model. Trained in tensorflow on ImageNet-1k by paper authors. Ported from official Tensorflow implementation (https://github.com/google-research/maxvit) to PyTorch by Ross Wightman. MaxxViT covers a number of related model architectures that share a common structure including: - CoAtNet - Combining MBConv (depthwise-separable) convolutional blocks in early stages with self-attention transformer blocks in later stages. - MaxViT - Uniform blocks across all stages, each containing a MBConv (depthwise-separable) convolution block followed by two self-attention blocks with different partitioning schemes (window followed by grid). - CoAtNeXt - A timm specific arch that uses ConvNeXt blocks in place of MBConv blocks in CoAtNet. All normalization layers are LayerNorm (no BatchNorm). - MaxxViT - A timm specific arch that uses ConvNeXt blocks in place of MBConv blocks in MaxViT. All normalization layers are LayerNorm (no BatchNorm). - MaxxViT-V2 - A MaxxViT variation that removes the window block attention leaving only ConvNeXt blocks and grid attention w/ more width to compensate. Aside from the major variants listed above, there are more subtle changes from model to model. Any model name with the string `rw` are `timm` specific configs w/ modelling adjustments made to favour PyTorch eager use. These were created while training initial reproductions of the models so there are variations. All models with the string `tf` are models exactly matching Tensorflow based models by the original paper authors with weights ported to PyTorch. This covers a number of MaxViT models. The official CoAtNet models were never released.
- test_convnext.r160_in1k↗
timm
- Unicom-Unified-Multimodal-Modeling-via-Compressed-Continuous-Semantic-Representations↗
腾讯
- Unichat-llama3-Chinese-8B↗
UnicomLLM
- Llama-3.2-3B-bnb-4bit↗
unsloth
- whisper-telugu-base↗
vasista22