Instructions to use lblod/decide-marked-segmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lblod/decide-marked-segmentation with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("lblod/decide-marked-segmentation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.model from lblod/decide-marked-segmentation: direct link, hf CLI and curl.
- Browser
- Download file 4.69 MB
-
https://huggingface.co/lblod/decide-marked-segmentation/resolve/main/tokenizer.model
- Command line
-
hf download hf://lblod/decide-marked-segmentation/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/lblod/decide-marked-segmentation/resolve/main/tokenizer.model
4.69 MB
- Xet hash:
- a81fa217b67ef4a1992b48a47651c27a2a19df419eafd1aad9c0bbd5ff49bde3
- Size of remote file:
- 4.69 MB
- SHA256:
- 1299c11d7cf632ef3b4e11937501358ada021bbdf7c47638d13c0ee982f2e79c
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