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Update app.py
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app.py
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@@ -69,41 +69,32 @@ tokenizer.padding_side = 'left'
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peft_config = PeftConfig.from_pretrained("Tonic/mistralmed", token="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")
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peft_model = MistralForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.1", trust_remote_code=True)
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peft_model = PeftModel.from_pretrained(peft_model, "Tonic/mistralmed", token="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")
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#Remove the memory function
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class ChatBot:
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def __init__(self):
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self.history = []
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def predict(self, user_input, system_prompt="You are an expert medical analyst:"):
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# Combine user input and system prompt
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formatted_input = f"<s>[INST]{system_prompt} {user_input}[/INST]"
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# Encode user input
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user_input_ids = tokenizer.encode(formatted_input, return_tensors="pt")
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# # Concatenate the user input with chat history
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# if len(self.history) > 0:
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# chat_history_ids = torch.cat([self.history, user_input_ids], dim=-1)
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# else:
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# chat_history_ids = user_input_ids
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#
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# Generate a response using the PEFT model
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# # Update chat history
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# self.history = chat_history_ids
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#
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# Decode and return the response
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bot = ChatBot()
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title = "๐๐ปํ ๋์ ๋ฏธ์คํธ๋๋ฉ๋ ์ฑํ
์ ์ค์ ๊ฒ์ ํ์ํฉ๋๋ค๐๐๐ปWelcome to Tonic's MistralMed Chat๐"
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description = "์ด ๊ณต๊ฐ์ ์ฌ์ฉํ์ฌ ํ์ฌ ๋ชจ๋ธ์ ํ
์คํธํ ์ ์์ต๋๋ค. [(Tonic/MistralMed)](https://huggingface.co/Tonic/MistralMed) ๋๋ ์ด ๊ณต๊ฐ์ ๋ณต์ ํ๊ณ ๋ก์ปฌ ๋๋ ๐คHuggingFace์์ ์ฌ์ฉํ ์ ์์ต๋๋ค. [Discord์์ ํจ๊ป ๋ง๋ค๊ธฐ ์ํด Discord์ ๊ฐ์
ํ์ญ์์ค](https://discord.gg/VqTxc76K3u). You can use this Space to test out the current model [(Tonic/MistralMed)](https://huggingface.co/Tonic/MistralMed) or duplicate this Space and use it locally or on ๐คHuggingFace. [Join me on Discord to build together](https://discord.gg/VqTxc76K3u)."
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examples = [["[Question:] What is the proper treatment for buccal herpes?", "You are a medicine and public health expert, you will
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fn=bot.predict,
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title=title,
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description=description,
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@@ -113,4 +104,4 @@ examples = [["[Question:] What is the proper treatment for buccal herpes?", "You
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theme="ParityError/Anime"
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)
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iface.launch()
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peft_config = PeftConfig.from_pretrained("Tonic/mistralmed", token="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")
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peft_model = MistralForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.1", trust_remote_code=True)
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peft_model = PeftModel.from_pretrained(peft_model, "Tonic/mistralmed", token="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")
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# Remove the memory function
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class ChatBot:
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def __init__(self):
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self.history = []
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def predict(self, user_input, system_prompt="You are an expert medical analyst:"):
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# Combine user input and system prompt
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formatted_input = f"<s>[INST]{system_prompt} {user_input}[/INST]"
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# Encode user input
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user_input_ids = tokenizer.encode(formatted_input, return_tensors="pt")
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# Generate a response using the PEFT model
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response = peft_model.generate(input_ids, max_length=512, pad_token_id=tokenizer.eos_token_id)
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# Decode and return the response
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response_text = tokenizer.decode(response[0], skip_special_tokens=True)
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return response_text
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bot = ChatBot()
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title = "๐๐ปํ ๋์ ๋ฏธ์คํธ๋๋ฉ๋ ์ฑํ
์ ์ค์ ๊ฒ์ ํ์ํฉ๋๋ค๐๐๐ปWelcome to Tonic's MistralMed Chat๐"
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description = "์ด ๊ณต๊ฐ์ ์ฌ์ฉํ์ฌ ํ์ฌ ๋ชจ๋ธ์ ํ
์คํธํ ์ ์์ต๋๋ค. [(Tonic/MistralMed)](https://huggingface.co/Tonic/MistralMed) ๋๋ ์ด ๊ณต๊ฐ์ ๋ณต์ ํ๊ณ ๋ก์ปฌ ๋๋ ๐คHuggingFace์์ ์ฌ์ฉํ ์ ์์ต๋๋ค. [Discord์์ ํจ๊ป ๋ง๋ค๊ธฐ ์ํด Discord์ ๊ฐ์
ํ์ญ์์ค](https://discord.gg/VqTxc76K3u). You can use this Space to test out the current model [(Tonic/MistralMed)](https://huggingface.co/Tonic/MistralMed) or duplicate this Space and use it locally or on ๐คHuggingFace. [Join me on Discord to build together](https://discord.gg/VqTxc76K3u)."
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examples = [["[Question:] What is the proper treatment for buccal herpes?", "You are a medicine and public health expert, you will receive a question, answer the question, and provide a complete answer"]]
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iface = gr.Interface(
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fn=bot.predict,
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title=title,
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description=description,
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theme="ParityError/Anime"
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)
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iface.launch()
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