Instructions to use mccaly/test2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mccaly/test2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="mccaly/test2")# Load model directly from transformers import AutoImageProcessor, UperNetForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("mccaly/test2") model = UperNetForSemanticSegmentation.from_pretrained("mccaly/test2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pretrained_model from mccaly/test2: direct link, hf CLI and curl.
- Browser
- Download file 20 Bytes
-
https://huggingface.co/mccaly/test2/resolve/main/pretrained_model
- Command line
-
hf download hf://mccaly/test2/pretrained_model
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curl -L -o pretrained_model https://huggingface.co/mccaly/test2/resolve/main/pretrained_model
20 Bytes
| ../pretrained_model/ |