Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use nateraw/food with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nateraw/food with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nateraw/food") 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("nateraw/food") model = AutoModelForImageClassification.from_pretrained("nateraw/food", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Try to fix pipeline
Browse files- config.json +1 -1
config.json
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@@ -224,5 +224,5 @@
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"num_hidden_layers": 12,
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"patch_size": 16,
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"torch_dtype": "float32",
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"transformers_version": "4.
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}
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"num_hidden_layers": 12,
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"patch_size": 16,
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"torch_dtype": "float32",
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"transformers_version": "4.8.1"
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}
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