Instructions to use M-A-E/russian_text_simplification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use M-A-E/russian_text_simplification with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("M-A-E/russian_text_simplification") model = AutoModelForSeq2SeqLM.from_pretrained("M-A-E/russian_text_simplification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from M-A-E/russian_text_simplification: direct link, hf CLI and curl.
- Browser
- Download file 2.64 MB
-
https://huggingface.co/M-A-E/russian_text_simplification/resolve/refs%2Fpr%2F2/tokenizer.json
- Command line
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hf download hf://M-A-E/russian_text_simplification@refs/pr/2/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/M-A-E/russian_text_simplification/resolve/refs%2Fpr%2F2/tokenizer.json
2.64 MB
File too large to display, you can check the raw version instead.