Instructions to use ProMeText/aquilign-multilingual-segmenter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProMeText/aquilign-multilingual-segmenter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ProMeText/aquilign-multilingual-segmenter")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ProMeText/aquilign-multilingual-segmenter") model = AutoModelForTokenClassification.from_pretrained("ProMeText/aquilign-multilingual-segmenter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model_name from ProMeText/aquilign-multilingual-segmenter: direct link, hf CLI and curl.
- Browser
- Download file 40 Bytes
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https://huggingface.co/ProMeText/aquilign-multilingual-segmenter/resolve/refs%2Fpr%2F2/model_name
- Command line
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hf download hf://ProMeText/aquilign-multilingual-segmenter@refs/pr/2/model_name
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curl -L -o model_name https://huggingface.co/ProMeText/aquilign-multilingual-segmenter/resolve/refs%2Fpr%2F2/model_name
40 Bytes
| google-bert/bert-base-multilingual-cased |