Instructions to use philldevcoder/my_awesome_food_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use philldevcoder/my_awesome_food_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="philldevcoder/my_awesome_food_model") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("philldevcoder/my_awesome_food_model") model = AutoModelForImageClassification.from_pretrained("philldevcoder/my_awesome_food_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 2
Browse files
model.safetensors
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