Instructions to use zhxdoka/bori-punct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zhxdoka/bori-punct with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="zhxdoka/bori-punct")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("zhxdoka/bori-punct") model = AutoModelForTokenClassification.from_pretrained("zhxdoka/bori-punct", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from zhxdoka/bori-punct: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/zhxdoka/bori-punct/resolve/main/tokenizer.json
- Command line
-
hf download hf://zhxdoka/bori-punct/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/zhxdoka/bori-punct/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 516f2fc365650acf148b86e45907397a0c35af523df9e2ea3f88e25c76c1f057
- Size of remote file:
- 17.1 MB
- SHA256:
- acbd420e2269cdc1ef45332d3d5c418be4aef6b8cb5a0b7ccae0893485307153
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