gangyeolkim
/

open-llama-2-ko-7b-summarization

@@ -1,201 +1,50 @@
----
-library_name: transformers
-tags: []
----
-# Model Card for Model ID
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+### 개요
+- 한국어 요약 Task를 수행하는 모델입니다.
+### Base Model
+- [beomi/llama-2-ko-7b](https://huggingface.co/beomi/llama-2-ko-7b)
+### Dataset
+AI hub에 있는 아래 요약 데이터 중 3만건을 샘플링하여 사용하였습니다.
+- [추상 요약 사실성 검증 데이터](https://www.aihub.or.kr/aihubdata/data/view.do?currMenu=115&topMenu=100&aihubDataSe=data&dataSetSn=71620)
+- [요약문 및 레포트 생성 데이터](https://www.aihub.or.kr/aihubdata/data/view.do?currMenu=115&topMenu=100&aihubDataSe=data&dataSetSn=582)
+- [문서요약 텍스트](https://www.aihub.or.kr/aihubdata/data/view.do?currMenu=115&topMenu=100&aihubDataSe=data&dataSetSn=97)
+- [도서자료 요약](https://www.aihub.or.kr/aihubdata/data/view.do?currMenu=115&topMenu=100&aihubDataSe=data&dataSetSn=9)
+### 라이브러리 설치
+```bash
+pip3 install transformers gradio vllm
+```
+### 예제 코드
+```python
+from vllm import LLM, SamplingParams
+from transformers import AutoTokenizer
+import gradio as gr
+import os
+model_path = "gangyeolkim/open-llama-2-ko-7b-summarization"
+sampling_params = SamplingParams(max_tokens=1024, temperature=0.1)
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+llm = LLM(model=model_path, tokenizer=model_path, tensor_parallel_size=1)
+def gen(text, history):
+    text = [
+            "### 원문:",
+            f"{text}\n",
+            "### 요약:\n",
+        ]
+    prompts = "\n".join(text)
+    outputs = llm.generate(prompts, sampling_params)
+    for output in outputs:
+        generated_text = output.outputs[0].text
+    return generated_text
+demo = gr.ChatInterface(gen)
+demo.launch(share=True)
+```