Instructions to use MoTHer-VTHR/VTHR-FT-ModelTree_3-Depth_2-Node_cyuPPhSC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MoTHer-VTHR/VTHR-FT-ModelTree_3-Depth_2-Node_cyuPPhSC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="MoTHer-VTHR/VTHR-FT-ModelTree_3-Depth_2-Node_cyuPPhSC") 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("MoTHer-VTHR/VTHR-FT-ModelTree_3-Depth_2-Node_cyuPPhSC") model = AutoModelForImageClassification.from_pretrained("MoTHer-VTHR/VTHR-FT-ModelTree_3-Depth_2-Node_cyuPPhSC", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e7cc7cc1b3d9ffd4cea11083eb14a6669e2f42c9283513cbf01b5f86c24e2cfd
- Size of remote file:
- 343 MB
- SHA256:
- a24a95011af1d47852fbc3cdc1d4acf517b4ea7527f6e5f43325fd5bbd299a8e
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