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Update app.py
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app.py
CHANGED
@@ -9,19 +9,19 @@ model_directory = "Tonic/mistralmed"
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# Instantiate the Models
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tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-v0.1", trust_remote_code=True)
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tokenizer.pad_token = tokenizer.eos_token
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tokenizer.padding_side = 'left'
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# Specify the configuration class for the model
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model_config = AutoConfig.from_pretrained(base_model_id)
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# Load the PEFT model with the specified configuration
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peft_model = AutoModelForCausalLM.from_pretrained(base_model_id, config=model_config)
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# Load the PEFT model
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peft_config = PeftConfig.from_pretrained("Tonic/mistralmed", token="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")
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peft_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.1")
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peft_model = PeftModel.from_pretrained(base_model, "Tonic/mistralmed", token="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")
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class ChatBot:
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@@ -42,7 +42,7 @@ class ChatBot:
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response = peft_model.generate(chat_history_ids, max_length=512, pad_token_id=tokenizer.eos_token_id)
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# Update chat history
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self.history =
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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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# Instantiate the Models
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tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-v0.1", trust_remote_code=True)
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#tokenizer.pad_token = tokenizer.eos_token
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#tokenizer.padding_side = 'left'
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# Specify the configuration class for the model
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#model_config = AutoConfig.from_pretrained(base_model_id)
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# Load the PEFT model with the specified configuration
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#peft_model = AutoModelForCausalLM.from_pretrained(base_model_id, config=model_config)
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# Load the PEFT model
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peft_config = PeftConfig.from_pretrained("Tonic/mistralmed", token="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")
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peft_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.1", trust_remote_code=True)
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peft_model = PeftModel.from_pretrained(base_model, "Tonic/mistralmed", token="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")
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class ChatBot:
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response = peft_model.generate(chat_history_ids, max_length=512, pad_token_id=tokenizer.eos_token_id)
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# Update chat history
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self.history = chat_history_ids
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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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