Instructions to use TalentoTechIA/davincii with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TalentoTechIA/davincii with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="TalentoTechIA/davincii") 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/davincii") model = AutoModelForImageClassification.from_pretrained("TalentoTechIA/davincii", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6744380a1af3bf078d41e6b1bf475250efc7d90594dc2250c5d8ba8bcb25b37f
- Size of remote file:
- 343 MB
- SHA256:
- 413a5984f35e3fc3bb9f1b5ae267f08de948b70a6b22a0083a939cd40fcb61db
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