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 best/optimizer.pt from ProMeText/aquilign-multilingual-segmenter: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/ProMeText/aquilign-multilingual-segmenter/resolve/refs%2Fpr%2F2/best/optimizer.pt
- Command line
-
hf download hf://ProMeText/aquilign-multilingual-segmenter@refs/pr/2/best/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/ProMeText/aquilign-multilingual-segmenter/resolve/refs%2Fpr%2F2/best/optimizer.pt
1.42 GB
- Xet hash:
- 6e0537d17e8cc382a2c4c643796aad802bcab9f9ca3b233335e67db989f2debd
- Size of remote file:
- 1.42 GB
- SHA256:
- 01ecfaf470ba0fe1e5e0b2cfefe3f71753eb891306a8e426e4256b61f1df412b
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