Update model name

README.md

@@ -12,7 +12,7 @@ The heuristic adapter discovered from the [super-adapter](https://huggingface.co
 ### Information
 
 - **Model name:** shears-llama-7b-50-cs-heuristic-adapter
-- **Base model:** [IntelLabs/Llama-1-7B-sparsity50](https://huggingface.co/IntelLabs/Llama-1-7B-sparsity50)
+- **Base model:** [IntelLabs/shears-llama-7b-50-base](https://huggingface.co/IntelLabs/shears-llama-7b-50-base)
 - **Sparsity:** 50%
 - **Domain:** Commonsense
 - **Subnetwork version:** Heuristic
@@ -61,14 +61,14 @@ def generate_prompt(instruction):
                     ### Response:
                     """
 
-base_model = AutoModelForCausalLM.from_pretrained("IntelLabs/Llama-1-7B-sparsity50")
+base_model = AutoModelForCausalLM.from_pretrained("IntelLabs/shears-llama-7b-50-base")
 model = PeftModel.from_pretrained(base_model, "IntelLabs/shears-llama-7b-50-cs-heuristic-adapter")
 model.eval()
 
 non_zero_params = sum([(param.data != 0).sum().item() for _, param in model.named_parameters()])
 print(f"Number of all non-zero parameters: {non_zero_params}")
 
-tokenizer = AutoTokenizer.from_pretrained("IntelLabs/Llama-1-7B-sparsity50")
+tokenizer = AutoTokenizer.from_pretrained("IntelLabs/shears-llama-7b-50-base")
 
 instruction = "Please choose the correct answer to the question: A cactus stem is used to store\n\nAnswer1: fruit "
         "Answer2: liquid Answer3: food Answer4: spines\n\nAnswer format: answer1/answer2/answer3/answer4"