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Update app.py
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app.py
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@@ -1,10 +1,12 @@
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import gradio as gr
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import torch
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from transformers import AutoTokenizer, AutoModel,
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# Use the base model's ID
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base_model_id = "mistralai/Mistral-7B-v0.1"
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# Load the fine-tuned model "Tonic/mistralmed"
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model = AutoModel.from_pretrained("Tonic/mistralmed", config=config)
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@@ -21,7 +23,7 @@ class ChatBot:
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new_user_input_ids = tokenizer.encode(input + tokenizer.eos_token, return_tensors="pt")
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flat_history = [item for sublist in self.history for item in sublist]
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flat_history_tensor = torch.tensor(flat_history).unsqueeze(dim=0)
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bot_input_ids = torch.cat([flat_history_tensor, new_user_input_ids], dim=-1) if self
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chat_history_ids = model.generate(bot_input_ids, max_length=2000, pad_token_id=tokenizer.eos_token_id)
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self.history.append(chat_history_ids[:, bot_input_ids.shape[-1]:].tolist()[0])
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response = tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)
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import gradio as gr
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import torch
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from transformers import AutoTokenizer, AutoModel, BertConfig # Use BertConfig for your Mistral model
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# Use the base model's ID
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base_model_id = "mistralai/Mistral-7B-v0.1"
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# Create a configuration object specific to the base model (you can replace with your model's actual configuration if available)
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config = BertConfig()
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# Load the fine-tuned model "Tonic/mistralmed"
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model = AutoModel.from_pretrained("Tonic/mistralmed", config=config)
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new_user_input_ids = tokenizer.encode(input + tokenizer.eos_token, return_tensors="pt")
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flat_history = [item for sublist in self.history for item in sublist]
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flat_history_tensor = torch.tensor(flat_history).unsqueeze(dim=0)
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bot_input_ids = torch.cat([flat_history_tensor, new_user_input_ids], dim=-1) if self history else new_user_input_ids
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chat_history_ids = model.generate(bot_input_ids, max_length=2000, pad_token_id=tokenizer.eos_token_id)
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self.history.append(chat_history_ids[:, bot_input_ids.shape[-1]:].tolist()[0])
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response = tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)
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