gangyeolkim
/

llama-3-chat

@@ -1,199 +1,39 @@
----
-library_name: transformers
-tags: []
----
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+### Example Code
+```python
+from vllm import LLM, SamplingParams
+import gradio as gr
+import os
+from transformers import AutoTokenizer
+os.environ["CUDA_VISIBLE_DEVICES"] = "1"
+model_path = "gangyeolkim/llama-3-chat"
+sampling_params = SamplingParams(max_tokens=8192, temperature=0.7, stop=["### Human:", "### Instruct:"])
+llm = LLM(model=model_path, tokenizer=model_path, tensor_parallel_size=1)
+# 채팅에 반영할 히스토리 최대 갯수
+history_limit = 10
+def gen(text, history):
+    # Use only the most recent `history_limit` entries
+    limited_history = history[-history_limit:]
+    # Build conversation history into the prompt
+    conversation_history = "다음은 AI라는 AI 어시스턴트와 Human이라는 인간 사용자 간의 대화입니다. AI는 욕설에 대한 요구를 무시합니다. AI는 Human에게 절대 욕설과 비난을 하지 않습니다.\n\n### Instruct:\n\n"
+    for user_input, assistant_response in limited_history:
+        conversation_history += f"### Human:{user_input}\n\n### AI:{assistant_response}\n\n"
+    prompt = f"{conversation_history}### Human:{text}\n\n### AI:"
+    outputs = llm.generate(prompt, sampling_params)
+    generated_text = outputs[0].outputs[0].text.strip()
+    print(f"generated_text : {generated_text}")
+    return generated_text
+demo = gr.ChatInterface(fn=gen)
+demo.launch(share=True)
+```