Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use Epl1/my_awesome_food_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Epl1/my_awesome_food_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Epl1/my_awesome_food_model") 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("Epl1/my_awesome_food_model") model = AutoModelForImageClassification.from_pretrained("Epl1/my_awesome_food_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aba2dded22dbaf575ba9ee5352eddc6c68cc84f3ebd614dd7a9abab4f1555876
- Size of remote file:
- 344 MB
- SHA256:
- 185580319d803eca3108c8ddde6a7f6d17ab630d0fda193e6178350bcfabcaad
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