readme: # ehdwns1516/bart_finetuned_xsum
  
  * This model has been trained as a [xsum dataset](https://huggingface.co/datasets/xsum).
  * Input text what you want to summarize.
  
  review generator DEMO: [Ainize DEMO](https://main-text-summarizer-ehdwns1516.endpoint.ainize.ai/)
  
  review generator API: [Ainize API](https://ainize.web.app/redirect?git_repo=https://github.com/ehdwns1516/text_summarizer)
  
  ## Overview
  
  Language model: [facebook/bart-large](https://huggingface.co/facebook/bart-large)
  
  Language: English
  
  Training data: [xsum dataset](https://huggingface.co/datasets/xsum)
  
  Code: See [Ainize Workspace](https://ainize.ai/workspace/create?imageId=hnj95592adzr02xPTqss&git=https://github.com/ehdwns1516/bart_finetuned_xsum-notebook)
  
  ## Usage
  ## In Transformers
  
  ```
  from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
  tokenizer = AutoTokenizer.from_pretrained("ehdwns1516/bart_finetuned_xsum")
  
  model = AutoModelForSeq2SeqLM.from_pretrained("ehdwns1516/bart_finetuned_xsum")
  
  summarizer = pipeline(
      "summarization",
      model="ehdwns1516/bart_finetuned_xsum",
      tokenizer=tokenizer
  )
  
  context = "your context"
  
  result = dict()
  result[0] = summarizer(context)[0]
  ```
  