Instructions to use facebook/mask2former-swin-tiny-ade-semantic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mask2former-swin-tiny-ade-semantic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="facebook/mask2former-swin-tiny-ade-semantic")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("facebook/mask2former-swin-tiny-ade-semantic", dtype="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2c2b3bcae558f462bd2c7f6289f72ca0886ad24ebbba413eeed7800426ba6b72
- Size of remote file:
- 190 MB
- SHA256:
- 97bb47771b1f679d0d8b2de75f2d48ce8ad53a60ab56d489c792d48ccb044500
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.