Update app.py

app.py

@@ -53,27 +53,20 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
 base_model_id = "tiiuae/falcon-7b-instruct"
 model_directory = "Tonic/GaiaMiniMed"
 
-
-
-
 # Instantiate the Tokenizer
-tokenizer = AutoTokenizer.from_pretrained("tiiuae/falcon-7b-instruct", trust_remote_code=True, padding_side="left")
+tokenizer = AutoTokenizer.from_pretrained(base_model_id, trust_remote_code=True, padding_side="left")
 # tokenizer = AutoTokenizer.from_pretrained("Tonic/mistralmed", trust_remote_code=True, padding_side="left")
-tokenizer.pad_token = tokenizer.eos_token
-tokenizer.padding_side = 'left'
-
+# tokenizer.pad_token = tokenizer.eos_token
+# tokenizer.padding_side = 'left'
 
 # Load the GaiaMiniMed model with the specified configuration
 # Load the Peft model with a specific configuration
 # Specify the configuration class for the model
-model_config = AutoConfig.from_pretrained(base_model_id)
+model_config = AutoConfig.from_pretrained(model_directory)
 # Load the PEFT model with the specified configuration
 peft_model = AutoModelForCausalLM.from_pretrained(model_directory, config=model_config)
-peft_model = PeftModel.from_pretrained(model=base_model_id, model_id=model_directory, trust_remote_code=True)
 peft_model = PeftModel.from_pretrained(peft_model, model_directory)
 
-
-
 # Specify the configuration class for the model
 #model_config = AutoConfig.from_pretrained(base_model_id)