Update README.md

README.md

@@ -27,33 +27,24 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
 def generate_response(prompt):
     """
     Generate a response from the model based on the input prompt.
-
     Args:
     prompt (str): Prompt for the model.
-
     Returns:
     str: The generated response from the model.
     """
-    # Tokenize the input prompt
+
     inputs = tokenizer(prompt, return_tensors="pt")
-    
-    # Generate output tokens
     outputs = model.generate(**inputs, max_new_tokens=512, eos_token_id=tokenizer.eos_token_id, pad_token_id=tokenizer.pad_token_id)
-
-    # Decode the generated tokens to a string
     response = tokenizer.decode(outputs[0], skip_special_tokens=True)
 
     return response
 
-
-# Load the model and tokenizer
 model_id = "macadeliccc/SOLAR-math-2x10.7b"
 tokenizer = AutoTokenizer.from_pretrained(model_id)
 model = AutoModelForCausalLM.from_pretrained(model_id, load_in_4bit=True)
 
 prompt = "Explain the proof of Fermat's Last Theorem and its implications in number theory."
 
-
 print("Response:")
 print(generate_response(prompt), "\n")
 ```