Instructions to use facebook/convnext-base-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/convnext-base-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/convnext-base-224") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("facebook/convnext-base-224") model = AutoModelForImageClassification.from_pretrained("facebook/convnext-base-224") - Inference
- Notebooks
- Google Colab
- Kaggle
Add model
Browse files- config.json +1 -0
- pytorch_model.bin +2 -2
config.json
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"model_type": "convnext",
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"num_channels": 3,
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"num_stages": 4,
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"torch_dtype": "float32",
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"transformers_version": "4.17.0.dev0"
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}
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"model_type": "convnext",
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"num_channels": 3,
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"num_stages": 4,
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"patch_size": 4,
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"torch_dtype": "float32",
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"transformers_version": "4.17.0.dev0"
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}
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pytorch_model.bin
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oid sha256:cb0a2fc07b6ed8e6725911c7072408e374ba0a86e6cdf0ad7d105153b62b507d
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size 354492753
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