Create README.md

README.md

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+---
+
+language:
+- ru
+tags:
+- summarization
+license: apache-2.0
+
+---
+
+# RuT5TelegramHeadlines
+
+## Model description
+
+Based on [rut5-base](https://huggingface.co/cointegrated/rut5-base) model
+
+## Intended uses & limitations
+
+#### How to use
+
+```python
+from transformers import AutoTokenizer, T5ForConditionalGeneration
+
+model_name = "IlyaGusev/rut5_telegram_headlines"
+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]
+
+headline = tokenizer.decode(output_ids, skip_special_tokens=True)
+print(headline)
+```
+
+## Training data
+
+- Dataset: [ru_all_split.tar.gz](https://www.dropbox.com/s/ykqk49a8avlmnaf/ru_all_split.tar.gz)
+
+## Training procedure
+
+- Training script: [train.py](https://github.com/IlyaGusev/summarus/blob/master/external/hf_scripts/train.py)