Image Classification
Transformers
TensorBoard
Safetensors
vit
Sychol
3_class
ViT
Generated from Trainer
Instructions to use Sychol/ViT_dog_food with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sychol/ViT_dog_food with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Sychol/ViT_dog_food") 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("Sychol/ViT_dog_food") model = AutoModelForImageClassification.from_pretrained("Sychol/ViT_dog_food", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Sychol/ViT_dog_food: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/Sychol/ViT_dog_food/resolve/main/training_args.bin
- Command line
-
hf download hf://Sychol/ViT_dog_food/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Sychol/ViT_dog_food/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- 20a59bd9884d14ab14caf8580d306502f93cdb6884330357e6a2186d84165515
- Size of remote file:
- 5.37 kB
- SHA256:
- 1cc6dc0fe73825b03ed18a53733f600e9330281fdf3b0ff817491b0fd08732c5
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