Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use suredream/my_awesome_food_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use suredream/my_awesome_food_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="suredream/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("suredream/my_awesome_food_model") model = AutoModelForImageClassification.from_pretrained("suredream/my_awesome_food_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from suredream/my_awesome_food_model: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/suredream/my_awesome_food_model/resolve/main/training_args.bin
- Command line
-
hf download hf://suredream/my_awesome_food_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/suredream/my_awesome_food_model/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- dd1e749ccb68fa674081f50df4963470d5f9aa8f1373f1076fa6d4d355dfa5ce
- Size of remote file:
- 5.11 kB
- SHA256:
- df37238e443f7d0f7e5d96a31ae717a5b36cff49fac743d97adaac0914eb76ad
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