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
Add model
Browse files- README.md +10 -0
- config.json +34 -0
- model.safetensors +3 -0
- pytorch_model.bin +3 -0
README.md
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---
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tags:
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- image-classification
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- timm
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- transformers
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pipeline_tag: image-classification
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library_name: timm
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license: apache-2.0
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---
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# Model card for my-timm-model
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config.json
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{
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"architecture": "naflexvit_base_patch16_siglip",
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"num_classes": 0,
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"num_features": 768,
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"global_pool": "avg",
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"pretrained_cfg": {
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"tag": "v2_webli",
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"custom_load": false,
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"input_size": [
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3,
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384,
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384
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],
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"fixed_input_size": false,
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"interpolation": "bicubic",
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"crop_pct": 1.0,
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"crop_mode": "center",
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"mean": [
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0.5,
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0.5,
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0.5
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],
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"std": [
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0.5,
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0.5,
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0.5
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],
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"num_classes": 0,
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"pool_size": null,
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"first_conv": "embeds.proj",
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"classifier": "head",
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"license": "apache-2.0"
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}
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:0cfd412861ef5c62fe267e446acd6207e301dd7f9df23162e61cd7f0cc545672
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size 343392952
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:90b6ebf7d2e94b388a5e5bd130f7e59ff00794928a0ca65130bc8d126a89a35d
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size 343438527
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