Image Classification
Transformers
TensorBoard
Safetensors
vit
LMH
3_class
ViT
Generated from Trainer
Instructions to use audgns/ViT_beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use audgns/ViT_beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="audgns/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("audgns/ViT_beans") model = AutoModelForImageClassification.from_pretrained("audgns/ViT_beans", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from audgns/ViT_beans: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/audgns/ViT_beans/resolve/main/training_args.bin
- Command line
-
hf download hf://audgns/ViT_beans/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/audgns/ViT_beans/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- b1a8f5b9f54615d41f8c85a57a6af998af9300b99ec60d0a8e2543ca44fd0db2
- Size of remote file:
- 5.18 kB
- SHA256:
- 74ed5d92cda91ec236696dd562b914aa9f902b238ef0b49e7cb67a391b4de7ab
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