Instructions to use ssale2/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ssale2/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ssale2/results") 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("ssale2/results") model = AutoModelForImageClassification.from_pretrained("ssale2/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ssale2/results: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/ssale2/results/resolve/main/training_args.bin
- Command line
-
hf download hf://ssale2/results/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ssale2/results/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 143261b3d82bd4e682328d8edd5fb423bc374689c6907bc6cf038d0bf2c64c63
- Size of remote file:
- 5.3 kB
- SHA256:
- 6aa26332a4fe8ce0512ab8591acc75521007f9577a7da8b3ded984e29e5a7c24
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