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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d26e4b44af8fbee54f81feb5dfe7e75478bf7f64971296ab4efebbd13ad4e762
- Size of remote file:
- 94.3 MB
- SHA256:
- 1732dda70cff66e0ece491236b6f6e6767b8f23993ce0ceb014ecd6dc1eb9fbc
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