Instructions to use bn22/my-timm-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use bn22/my-timm-model with timm:
import timm model = timm.create_model("hf_hub:bn22/my-timm-model", pretrained=True) - Transformers
How to use bn22/my-timm-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="bn22/my-timm-model") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("bn22/my-timm-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +1 -0
config.json
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"architecture": "naflexvit_base_patch16_siglip",
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"num_classes": 10861,
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"num_features": 384,
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"global_pool": "map",
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"pretrained_cfg": {
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"tag": "v2_webli",
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"architecture": "naflexvit_base_patch16_siglip",
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"num_classes": 10861,
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"num_features": 384,
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"embed_dim": 384,
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"global_pool": "map",
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"pretrained_cfg": {
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"tag": "v2_webli",
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