Instructions to use TalentoTechIA/ManuelQuiceno with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TalentoTechIA/ManuelQuiceno with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="TalentoTechIA/ManuelQuiceno") 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/ManuelQuiceno") model = AutoModelForImageClassification.from_pretrained("TalentoTechIA/ManuelQuiceno", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 71fb0fe39fac3400507d4ef602a63a5cf4b159b49b858aaa7c3267f5aabf251f
- Size of remote file:
- 5.37 kB
- SHA256:
- 55e925886e1e9508d10504011219d4dc1f748e65314be4580bb38e32976b6221
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