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:
- 9ddefd251ddf6198c631b62b860870f7bcf852433ceb5ae33ebfc0b108e33ba6
- Size of remote file:
- 3.58 kB
- SHA256:
- afc944b0e5dcf4a4b6aa833522dc7fd350e6db64080ec721ec9848f97d73d129
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