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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d45f98eca8f7d7ce6b9293c1bf687c6c6d661a4c44a9499ba584d90d182a7fb9
- Size of remote file:
- 343 MB
- SHA256:
- c4264ccbffc5754b96bfb306975094b8ee457362f934469a46f19150d58c2add
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