Instructions to use sungile/custom-object-test7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sungile/custom-object-test7 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="sungile/custom-object-test7")# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("sungile/custom-object-test7") model = SegformerForSemanticSegmentation.from_pretrained("sungile/custom-object-test7", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 63c91f0f73fe933922bf1b285bf5a26c59dd29fc4ba13bd9d7771bf11d2be303
- Size of remote file:
- 5.3 kB
- SHA256:
- c8290f5abef5cbb2c08fd6a5cd14b39238620b2e4dd974c0bc5fb1128316464b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.