Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use sanjeev498/vit-base-beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sanjeev498/vit-base-beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sanjeev498/vit-base-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("sanjeev498/vit-base-beans") model = AutoModelForImageClassification.from_pretrained("sanjeev498/vit-base-beans", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from sanjeev498/vit-base-beans: direct link, hf CLI and curl.
- Browser
- Download file 3.38 kB
-
https://huggingface.co/sanjeev498/vit-base-beans/resolve/main/training_args.bin
- Command line
-
hf download hf://sanjeev498/vit-base-beans/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sanjeev498/vit-base-beans/resolve/main/training_args.bin
3.38 kB
- Xet hash:
- d8524ec780402804650a7b12ed1c0747e5e7e5c60af56cbe3c5ed2baae94bf60
- Size of remote file:
- 3.38 kB
- SHA256:
- ee9a94d7a9f527bb3b7366cd7ba66ab49919923404c75e1fa4b21215c9ce544c
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