Instructions to use Wikidepia/albert-punctuation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Wikidepia/albert-punctuation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Wikidepia/albert-punctuation")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Wikidepia/albert-punctuation") model = AutoModelForTokenClassification.from_pretrained("Wikidepia/albert-punctuation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Wikidepia/albert-punctuation: direct link, hf CLI and curl.
- Browser
- Download file 44.4 MB
-
https://huggingface.co/Wikidepia/albert-punctuation/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Wikidepia/albert-punctuation/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Wikidepia/albert-punctuation/resolve/main/pytorch_model.bin
44.4 MB
- Xet hash:
- ba978fdff333338ce0a951c80458b9c15a5961e2a684d300d5dd6d682995f013
- Size of remote file:
- 44.4 MB
- SHA256:
- c502c71f1fde2c8f9b826c9049114f5448804fc0ac4b7e158801288d0fc2f47a
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