Instructions to use rak3/test_push_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rak3/test_push_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="rak3/test_push_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("rak3/test_push_model") model = AutoModelForImageClassification.from_pretrained("rak3/test_push_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1ed5b1203e82db63d967833e387aa5b7205fdd543a2dadb91df6fe138b825fec
- Size of remote file:
- 343 MB
- SHA256:
- 6cf8f5f7247449fd1abae773d49ad7f6d1fae647c8645e70c83056591ec7be65
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