Instructions to use vasudevgupta/mbart-summarizer-interiit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vasudevgupta/mbart-summarizer-interiit with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("vasudevgupta/mbart-summarizer-interiit") model = AutoModelForSeq2SeqLM.from_pretrained("vasudevgupta/mbart-summarizer-interiit") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
This model is trained as a part of InterIIT'21 competition, on the dataset provided by Bridgei2i. It is able to do multilingual (Hindi, English, Hinglish) summarization (many -> one) & is capable of generating summaries in English regardless of the input language.
| Rouge-L | Sacrebleu | Headline Similarity (using sentence-transformers) |
|---|---|---|
| p=0.46 r=0.49 f1=0.52 | 23.46 | 0.75 |
mBART is initialized from facebook/mbart-large-cc25 and is trained as per strategy mentioned in our GitHub.
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