Instructions to use TalentoTechIA/Rcalixto_24_05_25 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TalentoTechIA/Rcalixto_24_05_25 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="TalentoTechIA/Rcalixto_24_05_25") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("TalentoTechIA/Rcalixto_24_05_25") model = AutoModelForImageClassification.from_pretrained("TalentoTechIA/Rcalixto_24_05_25", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 79bc4377e89d059ddda6e1cc060dcae8a0cb3b88a327222e6c9610afd998b97a
- Size of remote file:
- 5.37 kB
- SHA256:
- 197916e0636e540450cd7e708debb46989b846e1d8b9ae993809a9c32aa5b288
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