Instructions to use SpotLab/MobileViT_DeepLabv3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SpotLab/MobileViT_DeepLabv3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="SpotLab/MobileViT_DeepLabv3")# Load model directly from transformers import AutoImageProcessor, MobileViTForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("SpotLab/MobileViT_DeepLabv3") model = MobileViTForSemanticSegmentation.from_pretrained("SpotLab/MobileViT_DeepLabv3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe3598be89de1d8eedf8b8cbdc4e25c16b9bf50e5cc22fcdb463a41fb2b5b0fb
- Size of remote file:
- 7.42 MB
- SHA256:
- 836d1d6b55ee4dabf7cc8fde30c61f3a2e2a4fe770bab04dd4ac4d738dd74d48
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.