Transformers
PyTorch
JAX
Safetensors
Russian
English
t5
text2text-generation
russian
text-generation-inference
Instructions to use cointegrated/rut5-base-multitask with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cointegrated/rut5-base-multitask with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("cointegrated/rut5-base-multitask") model = AutoModelForSeq2SeqLM.from_pretrained("cointegrated/rut5-base-multitask", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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This is a smaller version of the [google/mt5-base](https://huggingface.co/google/mt5-base) with only some Rusian and English embeddings left.
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The model has been fine-tuned for several tasks with sentences or short paragraphs:
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* translation (`translate ru-en` and `translate en-ru`)
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* Paraphrasing (`paraphrase`)
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This is a smaller version of the [google/mt5-base](https://huggingface.co/google/mt5-base) with only some Rusian and English embeddings left.
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More details are given in a Russian post: https://habr.com/ru/post/581932/
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The model has been fine-tuned for several tasks with sentences or short paragraphs:
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* translation (`translate ru-en` and `translate en-ru`)
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* Paraphrasing (`paraphrase`)
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