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---
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:
```python
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
- Dataset: [Gazeta](https://huggingface.co/datasets/IlyaGusev/gazeta)
## 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 |
|