Instructions to use macqueen01/sonigo-CLIP-tagger with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use macqueen01/sonigo-CLIP-tagger with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("macqueen01/sonigo-CLIP-tagger") model = AutoModel.from_pretrained("macqueen01/sonigo-CLIP-tagger", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload model
Browse files- config.json +2 -2
- model.safetensors +2 -2
config.json
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{
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"_name_or_path": "openai/clip-vit-base-patch32",
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"architectures": [
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"
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],
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"initializer_factor": 1.0,
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"logit_scale_init_value": 2.6592,
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"model_type": "clip_text_model"
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},
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"torch_dtype": "float32",
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"transformers_version": "4.46.
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"vision_config": {
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"dropout": 0.0,
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"model_type": "clip_vision_model"
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{
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"_name_or_path": "openai/clip-vit-base-patch32",
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"architectures": [
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"SoftmaxCLIPModel"
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],
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"initializer_factor": 1.0,
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"logit_scale_init_value": 2.6592,
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"model_type": "clip_text_model"
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},
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"torch_dtype": "float32",
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"transformers_version": "4.46.3",
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"vision_config": {
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"dropout": 0.0,
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"model_type": "clip_vision_model"
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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size 613562732
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