Transformers
PyTorch
Russian
t5
text2text-generation
Simplification
Summarization
paraphrase
text-generation-inference
Instructions to use DmitriyVasiliev/ruT5-base-simplification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DmitriyVasiliev/ruT5-base-simplification with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("DmitriyVasiliev/ruT5-base-simplification") model = AutoModelForSeq2SeqLM.from_pretrained("DmitriyVasiliev/ruT5-base-simplification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 66768e9c1b982f6c153634069213eef1a0e53de36461037f4ab7c30ff333620d
- Size of remote file:
- 892 MB
- SHA256:
- cadeafa544361e72c161d835c9fc05da5ee12aafd0345816d6104a6a80ea82fe
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