Instructions to use MrPotato/ReferenceSegmentationLarge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MrPotato/ReferenceSegmentationLarge with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="MrPotato/ReferenceSegmentationLarge", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("MrPotato/ReferenceSegmentationLarge", trust_remote_code=True) model = AutoModelForTokenClassification.from_pretrained("MrPotato/ReferenceSegmentationLarge", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1ec35298a5abd3054f9d66e08ac660a17ff2904a7cf24abbed5d3eca40da8b06
- Size of remote file:
- 2.24 GB
- SHA256:
- 80eda6ae367a14d96350548bef5bf6547e6ca27d1ef7f366bd18434c0fce5d19
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