Instructions to use MoTHer-VTHR/VTHR-FT-ModelTree_3-Depth_2-Node_nHLuE7zf 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_nHLuE7zf 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_nHLuE7zf") 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_nHLuE7zf") model = AutoModelForImageClassification.from_pretrained("MoTHer-VTHR/VTHR-FT-ModelTree_3-Depth_2-Node_nHLuE7zf", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b94d8c89333ab6056f5ebbc9e095f3bdd53922692bb3f5bad6b3eb7423d82e74
- Size of remote file:
- 343 MB
- SHA256:
- 61623af5ba6f2664fc2c6f8182c82bea56407670877745514943a1e1dda7e014
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