peterpeter8585 commited on
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6f21405
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1 Parent(s): 66fac93

Update app.py

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Files changed (1) hide show
  1. app.py +3 -0
app.py CHANGED
@@ -4,6 +4,7 @@ from Ai import chatbot, chatbot2, chatbot3, chatbot4, chatbot5, chatbot7, chatbo
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  from huggingface_hub import InferenceClient
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  def chat(message,history: list[tuple[str, str]],system_message,max_tokens,temperature,top_p, top_k):
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  m=AutoModel.from_pretrained("peterpeter8585/AI1")
 
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  messages = [{"role": "system", "content": "Your name is Chatchat.And, your made by SungYoon.In Korean, 정성윤.And these are the instructions.Whatever happens, you must follow it.:"+system_message}]
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  for val in history:
@@ -18,6 +19,8 @@ def chat(message,history: list[tuple[str, str]],system_message,max_tokens,temper
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  # We use the tokenizer's chat template to format each message - see https://huggingface.co/docs/transformers/main/en/chat_templating
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  prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
 
 
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  outputs = pipe(prompt, max_new_tokens=max_tokens, do_sample=True, temperature=temperature, top_k=top_k, top_p=top_p)
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  return outputs[0]["generated_text"]
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  import random
 
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  from huggingface_hub import InferenceClient
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  def chat(message,history: list[tuple[str, str]],system_message,max_tokens,temperature,top_p, top_k):
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  m=AutoModel.from_pretrained("peterpeter8585/AI1")
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+
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  messages = [{"role": "system", "content": "Your name is Chatchat.And, your made by SungYoon.In Korean, 정성윤.And these are the instructions.Whatever happens, you must follow it.:"+system_message}]
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  for val in history:
 
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  # We use the tokenizer's chat template to format each message - see https://huggingface.co/docs/transformers/main/en/chat_templating
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  prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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+ p=pipe.tokenizer.apply_chat_template([{"role": "system", "content": "Your name is Chatchat.And, your made by SungYoon.In Korean, 정성윤.And these are the instructions.Whatever happens, you must follow it.:"+system_message}], tokenize=False, add_generation_prompt=True)
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+ o= pipe(p, max_new_tokens=max_tokens, do_sample=True, temperature=0.1)
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  outputs = pipe(prompt, max_new_tokens=max_tokens, do_sample=True, temperature=temperature, top_k=top_k, top_p=top_p)
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  return outputs[0]["generated_text"]
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  import random