Instructions to use TalentoTechIA/william_Rosero with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TalentoTechIA/william_Rosero with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="TalentoTechIA/william_Rosero") 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("TalentoTechIA/william_Rosero") model = AutoModelForImageClassification.from_pretrained("TalentoTechIA/william_Rosero", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from TalentoTechIA/william_Rosero: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/TalentoTechIA/william_Rosero/resolve/main/training_args.bin
- Command line
-
hf download hf://TalentoTechIA/william_Rosero/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/TalentoTechIA/william_Rosero/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- b6e90791537071a83040baa1b7ad259688a74c6aecad2a3b3317c19db74bfd0c
- Size of remote file:
- 5.37 kB
- SHA256:
- 1ad2c91e2ba59165e05469e3aa3fffe5215a3aef254a1d80d9d907e901705b44
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