README

README.md

@@ -0,0 +1,84 @@
+---
+language:
+- ru
+tags:
+- summarization
+- mbart
+license: apache-2.0
+---
+
+# MBARTRuSumGazeta
+
+## Model description
+
+This is a ported version of [fairseq model](https://www.dropbox.com/s/fijtntnifbt9h0k/gazeta_mbart_v2_fairseq.tar.gz).
+
+For more details, please see, [Dataset for Automatic Summarization of Russian News](https://arxiv.org/abs/2006.11063).
+
+## Intended uses & limitations
+
+#### How to use
+
+```python
+from transformers import MBartTokenizer, MBartForConditionalGeneration
+
+article_text = "..."
+model_name = "IlyaGusev/mbart_ru_sum_gazeta"
+tokenizer = MBartTokenizer.from_pretrained(model_name)
+model = MBartForConditionalGeneration.from_pretrained(model_name)
+
+input_ids = tokenizer.prepare_seq2seq_batch(
+    [source],
+    src_lang="en_XX",
+    return_tensors="pt",
+    padding="max_length",
+    truncation=True,
+    max_length=600
+)["input_ids"][0]
+
+output_ids = model.generate(
+    input_ids=input_ids.unsqueeze(0),
+    max_length=162,
+    no_repeat_ngram_size=3,
+    num_beams=5,
+    top_k=0,
+    decoder_start_token_id=tokenizer.lang_code_to_id["ru_RU"]
+)[0]
+summary = tokenizer.decode(output_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)
+print(summary)
+```
+
+#### Limitations and bias
+
+- The model should work well with Gazeta.ru articles, but for any other agencies it can suffer from domain change
+
+
+## Training data
+
+- Dataset: https://github.com/IlyaGusev/gazeta
+
+## Training procedure
+
+- Fairseq training script: https://github.com/IlyaGusev/summarus/blob/master/external/bart_scripts/train.sh
+- Porting: https://colab.research.google.com/drive/13jXOlCpArV-lm4jZQ0VgOpj6nFBYrLAr
+
+## Eval results
+
+
+### BibTeX entry and citation info
+
+```bibtex
+@InProceedings{10.1007/978-3-030-59082-6_9,
+author="Gusev, Ilya",
+editor="Filchenkov, Andrey
+and Kauttonen, Janne
+and Pivovarova, Lidia",
+title="Dataset for Automatic Summarization of Russian News",
+booktitle="Artificial Intelligence and Natural Language",
+year="2020",
+publisher="Springer International Publishing",
+address="Cham",
+pages="122--134",
+isbn="978-3-030-59082-6"
+}
+```