Image Classification
Transformers
TensorBoard
Safetensors
vit
image=classification
ViT
Generated from Trainer
Instructions to use Developer9215/vit-base-beans-demo-v5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Developer9215/vit-base-beans-demo-v5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Developer9215/vit-base-beans-demo-v5") 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("Developer9215/vit-base-beans-demo-v5") model = AutoModelForImageClassification.from_pretrained("Developer9215/vit-base-beans-demo-v5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Developer9215/vit-base-beans-demo-v5: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/Developer9215/vit-base-beans-demo-v5/resolve/main/training_args.bin
- Command line
-
hf download hf://Developer9215/vit-base-beans-demo-v5/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Developer9215/vit-base-beans-demo-v5/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- 984acd3a3b575ecb68b176346be52db601c52a0ef4c2dad7a0a65907bbe6fe85
- Size of remote file:
- 5.37 kB
- SHA256:
- 033db351715120211df7eb8574de5df785bf5f0d9b71671034b0cb90048f9ac5
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