Instructions to use apple/deeplabv3-mobilevit-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apple/deeplabv3-mobilevit-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="apple/deeplabv3-mobilevit-small")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, MobileViTForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("apple/deeplabv3-mobilevit-small") model = MobileViTForSemanticSegmentation.from_pretrained("apple/deeplabv3-mobilevit-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from apple/deeplabv3-mobilevit-small: direct link, hf CLI and curl.
- Browser
- Download file 25.6 MB
-
https://huggingface.co/apple/deeplabv3-mobilevit-small/resolve/refs%2Fpr%2F2/pytorch_model.bin
- Command line
-
hf download hf://apple/deeplabv3-mobilevit-small@refs/pr/2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/apple/deeplabv3-mobilevit-small/resolve/refs%2Fpr%2F2/pytorch_model.bin
25.6 MB
- Xet hash:
- f336008d9eff9e38a693aad66902cc8a8416ae23e6177ab44ede4c1379a42dc7
- Size of remote file:
- 25.6 MB
- SHA256:
- 5e68a534df237d8b89aa9209c815976b4b34f49a4e8107f630fd799697e98291
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