Image Classification
Transformers
TensorBoard
Safetensors
vit
JIH
3_Class
ViT
Generated from Trainer
Instructions to use jih123/ViT_beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jih123/ViT_beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jih123/ViT_beans") 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("jih123/ViT_beans") model = AutoModelForImageClassification.from_pretrained("jih123/ViT_beans", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jih123/ViT_beans: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/jih123/ViT_beans/resolve/main/training_args.bin
- Command line
-
hf download hf://jih123/ViT_beans/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jih123/ViT_beans/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- 7665f9e235d5e1cf0c73fbd62082f1fb179a8298dbd93904443461a0362b6e57
- Size of remote file:
- 5.37 kB
- SHA256:
- 8400c913145a511b5416dd0e21bad143e22451d371247687a10ee38ddffc531c
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