Instructions to use addy88/perceiver_image_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use addy88/perceiver_image_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="addy88/perceiver_image_classifier") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoTokenizer, AutoModelForImageClassification tokenizer = AutoTokenizer.from_pretrained("addy88/perceiver_image_classifier") model = AutoModelForImageClassification.from_pretrained("addy88/perceiver_image_classifier") - Notebooks
- Google Colab
- Kaggle
add model
Browse files- config.json +1 -1
- pytorch_model.bin +2 -2
config.json
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"architectures": [
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"PerceiverForImageClassificationLearned"
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"_name_or_path": "/content/mymodel",
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"architectures": [
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"PerceiverForImageClassificationLearned"
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pytorch_model.bin
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size 245389351
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