Instructions to use Transformers123/roboflow_20 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Transformers123/roboflow_20 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("Transformers123/roboflow_20") model = SegformerForSemanticSegmentation.from_pretrained("Transformers123/roboflow_20", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Transformers123/roboflow_20: direct link, hf CLI and curl.
- Browser
- Download file 14.9 MB
-
https://huggingface.co/Transformers123/roboflow_20/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Transformers123/roboflow_20/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Transformers123/roboflow_20/resolve/main/pytorch_model.bin
14.9 MB
- Xet hash:
- 87bd443328fb569c8373357b7284e6b3e7b693cb176162c20b5d486d9409dcc8
- Size of remote file:
- 14.9 MB
- SHA256:
- 6c02044e8d3ebe20be9483f906f23d55164cc2099915534914e89170517a1d5f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.