pytorch bart seq2seq en transformers summarization text2text-generation
.gitattributes README.md config.json merges.txt pytorch_model.bin special_tokens_map.json tokenizer_config.json vocab.json
---
language: "en"
tags:
- summarization
---
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# Summarization
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## Model description
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BartForConditionalGeneration model fine tuned for summarization on 10000 samples from the cnn-dailymail dataset
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## How to use
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PyTorch model available
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```python
from transformers import AutoTokenizer, AutoModelWithLMHead, pipeline
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tokenizer = AutoTokenizer.from_pretrained("yuvraj/summarizer-cnndm") 
AutoModelWithLMHead.from_pretrained("yuvraj/summarizer-cnndm")
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summarizer = pipeline('summarization', model=model, tokenizer=tokenizer)
summarizer("<Text to be summarized>")
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## Limitations and bias
Trained on a small dataset
