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mlenjoyneer
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rut5_large_sum_gazeta

Text2Text Generation
Transformers
PyTorch
Russian
t5
text-generation-inference
Inference Endpoints
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metadata
language: ru
license: apache-2.0
datasets:
  - IlyaGusev/gazeta

RuT5LargeSumGazeta

Model description

This is the model for abstractive summarization for Russian based on ai-forever/ruT5-large.

Intended uses & limitations

How to use

Here is how to use this model in PyTorch:

from transformers import AutoTokenizer, T5ForConditionalGeneration

model_name = "mlenjoyneer/rut5_large_sum_gazeta"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = T5ForConditionalGeneration.from_pretrained(model_name)

article_text = "..."

input_ids = tokenizer(
    [article_text],
    max_length=600,
    add_special_tokens=True,
    padding="max_length",
    truncation=True,
    return_tensors="pt"
)["input_ids"]

output_ids = model.generate(
    input_ids=input_ids,
    no_repeat_ngram_size=4
)[0]

summary = tokenizer.decode(output_ids, skip_special_tokens=True)
print(summary)

Training data

Evaluation results

Model R-1-f R-2-f R-L-f chrF BLEU Avg char length
IlyaGusev/mbart_ru_sum_gazeta 28.7 11.1 24.4 37.3 9.4 373
IlyaGusev/rut5_base_sum_gazeta 28.6 11.1 24.5 37.2 9.4 331
IlyaGusev/rugpt3medium_sum_gazeta 24.1 6.5 19.8 32.1 3.6 242
rut5-large_sum_gazeta 29.6 11.7 25.2 37.3 9.4 304