Instructions to use ProbeX/Model-J__SupViT__model_idx_0103 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProbeX/Model-J__SupViT__model_idx_0103 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__SupViT__model_idx_0103") 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("ProbeX/Model-J__SupViT__model_idx_0103") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0103", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ProbeX/Model-J__SupViT__model_idx_0103: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/ProbeX/Model-J__SupViT__model_idx_0103/resolve/main/training_args.bin
- Command line
-
hf download hf://ProbeX/Model-J__SupViT__model_idx_0103/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ProbeX/Model-J__SupViT__model_idx_0103/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- e25e4948d7d46e3ec8246cb1de50257cbb789afdc109818c7580963148a2e532
- Size of remote file:
- 5.37 kB
- SHA256:
- a8684ef776f1611696899678c5253b066e6bf13fc43628f651e7963b4a3dae8d
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