Update README.md

README.md

@@ -9,17 +9,16 @@ base_model:
 ---
 ## Usage
 Support for this model will be added in the upcoming transformers release. In the meantime, please install the library from source:
-'''
+~~~
 pip install transformers
-
-'''
+~~~
 We can now run inference on this model:
-'''
+~~~
 import torch
 from transformers import AutoTokenizer, AutoModelForCausalLM
 
 # Load the tokenizer and model
-model_path = "nvidia/Mistral-NeMo-Minitron-8B-Base"
+model_path = "YaoLuzjut/partial-layer_fine-tuning_Llama-3.1-8B-Instruct"
 tokenizer = AutoTokenizer.from_pretrained(model_path)
 
 device = 'cuda'
@@ -36,8 +35,7 @@ outputs = model.generate(inputs, max_length=20)
 # Decode and print the output
 output_text = tokenizer.decode(outputs[0])
 print(output_text)
-
-'''
+~~~
 
 ## Evaluation Results
 Zero-shot performance. Evaluated using select datasets from the [LM Evaluation Harness](https://github.com/EleutherAI/lm-evaluation-harness/tree/main) with additions: