Update app.py

app.py

@@ -3,7 +3,7 @@ from peft import PeftModel, PeftConfig
 from transformers import AutoModelForCausalLM, AutoTokenizer
 import torch
 
-'''
+
 if torch.cuda.is_available():
     device = torch.device("cuda")
     print("GPU is available!")
@@ -19,32 +19,6 @@ tokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path)
 
 # Load the Lora model
 model = PeftModel.from_pretrained(model, peft_model_id)
-'''
-
-import torch
-from peft import PeftModel, PeftConfig
-from transformers import AutoModelForCausalLM, AutoTokenizer
-
-if torch.cuda.is_available():
-    device = torch.device("cuda")
-    print("GPU is available!")
-else:
-    device = torch.device("cpu")
-    print("GPU is not available, using CPU.")
-
-peft_model_id = "phearion/bigbrain-v0.0.1"
-config = PeftConfig.from_pretrained(peft_model_id)
-model = AutoModelForCausalLM.from_pretrained(
-    config.base_model_name_or_path,                          
-    low_cpu_mem_usage=True,
-    return_dict=True,
-    torch_dtype=torch.bfloat16)
-
-tokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path)
-
-# Load the Lora model
-model = PeftModel.from_pretrained(model, peft_model_id)
-model = model.merge_and_unload()
 
 def greet(text):
     batch = tokenizer("“aide moi avec les equa diff ” ->: ", return_tensors='pt')