Instructions to use TalentoTechIA/juanprueba with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TalentoTechIA/juanprueba with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="TalentoTechIA/juanprueba") 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/juanprueba") model = AutoModelForImageClassification.from_pretrained("TalentoTechIA/juanprueba", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from TalentoTechIA/juanprueba: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/TalentoTechIA/juanprueba/resolve/main/training_args.bin
- Command line
-
hf download hf://TalentoTechIA/juanprueba/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/TalentoTechIA/juanprueba/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- a84408c7a84bb374c39ba36493060184a07ea933a69d8b0a1b222e31ef60bed9
- Size of remote file:
- 5.3 kB
- SHA256:
- 43167ae08e44ea675c38504b834bef60086e06d80d814cc159dc0e3c71879686
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