Create README.md

README.md

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+# 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]
+```