Token Classification
Transformers
Safetensors
Italian
English
xlm-roberta
sentence-boundary-detection
sentence-splitting
multilingual
Instructions to use LorenzoVentrone/SentenceSplitter-it-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LorenzoVentrone/SentenceSplitter-it-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="LorenzoVentrone/SentenceSplitter-it-en")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("LorenzoVentrone/SentenceSplitter-it-en") model = AutoModelForTokenClassification.from_pretrained("LorenzoVentrone/SentenceSplitter-it-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from LorenzoVentrone/SentenceSplitter-it-en: direct link, hf CLI and curl.
- Browser
- Download file 16.8 MB
-
https://huggingface.co/LorenzoVentrone/SentenceSplitter-it-en/resolve/main/tokenizer.json
- Command line
-
hf download hf://LorenzoVentrone/SentenceSplitter-it-en/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/LorenzoVentrone/SentenceSplitter-it-en/resolve/main/tokenizer.json
16.8 MB
- Xet hash:
- 3b1ba183d64c8c90a4d3ec00327e791b50e32cfb3f438c379267b31a92e9212c
- Size of remote file:
- 16.8 MB
- SHA256:
- 9aa6cb9642061cf6d0a38a953b46b51d283a146d2b32edd791c2c0af45999418
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