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")# pip install -U transformers accelerate # 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
Download optimizer.pt from ayang903/ds340: direct link, hf CLI and curl.
- Browser
- Download file 687 MB
-
https://huggingface.co/ayang903/ds340/resolve/refs%2Fpr%2F2/optimizer.pt
- Command line
-
hf download hf://ayang903/ds340@refs/pr/2/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/ayang903/ds340/resolve/refs%2Fpr%2F2/optimizer.pt
687 MB
- Xet hash:
- 684919932ed65c31850b08842c554ad9b52207ee27049c02a2724945530fbc8c
- Size of remote file:
- 687 MB
- SHA256:
- bc2a31527103ba6d74cbd6e1a96ac2fe36cb3a45d361f68a42136eb115824308
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