Instructions to use ayang903/ds340 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ayang903/ds340 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ayang903/ds340") 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("ayang903/ds340") model = AutoModelForImageClassification.from_pretrained("ayang903/ds340") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 33c9bedaf2c13eeacdc33521207aab7cb4babdf67e2f2d81ad857fe6fe3ceea2
- Size of remote file:
- 627 Bytes
- SHA256:
- 4f0051d0af53410e29e0c7de2401abe0dfdff6e124db2e23d7a56174ecb2db4c
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