Instructions to use MoTHer-VTHR/VTHR-FT-ModelTree_2-Depth_2-Node_gbsFAQSL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MoTHer-VTHR/VTHR-FT-ModelTree_2-Depth_2-Node_gbsFAQSL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="MoTHer-VTHR/VTHR-FT-ModelTree_2-Depth_2-Node_gbsFAQSL") 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_2-Depth_2-Node_gbsFAQSL") model = AutoModelForImageClassification.from_pretrained("MoTHer-VTHR/VTHR-FT-ModelTree_2-Depth_2-Node_gbsFAQSL", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c3131300b1e105c770fd348cb716df2f15a0d91fdaf9194372b6f19fb9afbe6e
- Size of remote file:
- 343 MB
- SHA256:
- 92f30c7b975bf6ffa8b0010e724f8198c8535bcbf3cfd5cdc6051de68a9aa714
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