Instructions to use CVPROJ25/FINETUNED with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CVPROJ25/FINETUNED with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="CVPROJ25/FINETUNED") 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("CVPROJ25/FINETUNED") model = AutoModelForImageClassification.from_pretrained("CVPROJ25/FINETUNED", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from CVPROJ25/FINETUNED: direct link, hf CLI and curl.
- Browser
- Download file 4.79 kB
-
https://huggingface.co/CVPROJ25/FINETUNED/resolve/main/training_args.bin
- Command line
-
hf download hf://CVPROJ25/FINETUNED/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CVPROJ25/FINETUNED/resolve/main/training_args.bin
4.79 kB
- Xet hash:
- 7bb15a78e7d53a0aafae2e7f40915f55cf56069f85aa0e11533868a9a6c3d41c
- Size of remote file:
- 4.79 kB
- SHA256:
- 15bd58ced891c43674dae43ad5d77ad1ff23c75b4ce3fd15a3acd656eaa2e3e6
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