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:
- c735ae37c0a6463592defeccc7d2b1291c5b0d3341add81385b5b917127185f7
- Size of remote file:
- 4.86 kB
- SHA256:
- 65fb581434164e984a977eb6c5dc47b47c496d9a999c96f046795260b50cb8a1
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