Instructions to use cppgohan/my_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cppgohan/my_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="cppgohan/my_model") 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("cppgohan/my_model") model = AutoModelForImageClassification.from_pretrained("cppgohan/my_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a212546164ee7425a3da03ee8011deeac92a30b6a7adfdf7763442de89ae013e
- Size of remote file:
- 4.86 kB
- SHA256:
- 260a8b91772990a28fd068a965be19ebcec4d3279a65a945555d98d039a6d876
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