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  # T5 for belarusian language
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  This model is based on T5-small with sequence length equal 128 tokens. Model trained from scratch on RTX 3090 24GB.
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  # Supported tasks:
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  result = model.generate(x, return_dict_in_generate=True, output_scores=True,max_length=128)
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  print(tokenizer.decode(result["sequences"][0]))
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  ```
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- </details>
 
 
 
 
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  # T5 for belarusian language
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+ ![model image](https://camo.githubusercontent.com/623b4dea0b653f2ad3f36c71ebfe749a677ac0a1/68747470733a2f2f6d69726f2e6d656469756d2e636f6d2f6d61782f343030362f312a44304a31674e51663876727255704b657944387750412e706e67)
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+
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  This model is based on T5-small with sequence length equal 128 tokens. Model trained from scratch on RTX 3090 24GB.
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  # Supported tasks:
 
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  result = model.generate(x, return_dict_in_generate=True, output_scores=True,max_length=128)
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  print(tokenizer.decode(result["sequences"][0]))
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  ```
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+ </details>
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+
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+ # References
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+ - [Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://jmlr.org/papers/volume21/20-074/20-074.pdf)