Instructions to use Wi11Chan/custom-myswin4seg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Wi11Chan/custom-myswin4seg with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Wi11Chan/custom-myswin4seg", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("Wi11Chan/custom-myswin4seg", trust_remote_code=True) model = AutoModelForSemanticSegmentation.from_pretrained("Wi11Chan/custom-myswin4seg", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from Wi11Chan/custom-myswin4seg: direct link, hf CLI and curl.
- Browser
- Download file 296 Bytes
-
https://huggingface.co/Wi11Chan/custom-myswin4seg/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://Wi11Chan/custom-myswin4seg/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/Wi11Chan/custom-myswin4seg/resolve/main/preprocessor_config.json
296 Bytes
| { | |
| "do_normalize": true, | |
| "do_resize": true, | |
| "feature_extractor_type": "ViTFeatureExtractor", | |
| "image_mean": [ | |
| 0.485, | |
| 0.456, | |
| 0.406 | |
| ], | |
| "image_std": [ | |
| 0.229, | |
| 0.224, | |
| 0.225 | |
| ], | |
| "reduce_labels": true, | |
| "resample": 2, | |
| "size": 512 | |
| } |