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, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8f41f36658960a3c2b8a132e32436e4816ac25e8e3c1c5430e25869acd7c2787
- Size of remote file:
- 2.24 GB
- SHA256:
- bc7dbcc9cd8cad6d81cba90b6b3e510410adfb3c9a8ab28fbca81708bd63688c
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