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:
- 5da646076101c2ac7e73f7c19c23f6583bc04fafdaddb7dcda5184834c8c549a
- Size of remote file:
- 5.37 kB
- SHA256:
- a9f25ff4700c17d8f76fcdaf75feab0da1a0863975d8220a8727e2eb2626acb3
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