checking write key

app.py

@@ -24,23 +24,6 @@ tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-v0.1")
 model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.1")
 
 
-#tokenizer = AutoTokenizer.from_pretrained("meta-llama/Meta-Llama-3-8B")
-#model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3-8B")
-
-
-# Define the directory to save the model
-#save_directory = "models"
-
-# Save the tokenizer and model to the specified directory
-#Run once
-#model.save_pretrained(save_directory)
-#tokenizer.save_pretrained(save_directory)
-
-# Load the tokenizer and model from the saved directory
-#tokenizer = AutoTokenizer.from_pretrained(save_directory, local_files_only=True,load_in_8bit=True,)
-#model = AutoModelForCausalLM.from_pretrained(save_directory, local_files_only=True,load_in_8bit=True)    
-
-
 
 
 pipe = pipeline("text-generation", 
@@ -52,17 +35,6 @@ pipe = pipeline("text-generation",
 result = pipe("tell me about transformer.", max_length=50, truncation=True)
 print(result)
 
-#Using  mistralai/Mistral-7B-Instruct-v0.2
-
-#save_directory = 'Mistral-7B-Instruct-v0.2'
-
-#tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2")
-#model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2") 
-
-
-#tokenizer = AutoTokenizer.from_pretrained(save_directory, local_files_only=True,load_in_8bit=True,)
-#model = AutoModelForCausalLM.from_pretrained(save_directory, local_files_only=True,load_in_8bit=True)
-
 
 pipe = pipeline("text-generation",  
                 model=model,        #'Mistral-7B-Instruct-v0.2'
@@ -70,6 +42,8 @@ pipe = pipeline("text-generation",
                 )
 
 
+
+
 question =st.text_input("enter your question","tell me about transformer.") 
 
 # Generate text using the pipeline