Update README.md

README.md

@@ -24,19 +24,21 @@ base_model: unsloth/llama-3-8b-Instruct-bnb-4bit
   ```
   
   ```
-    <!-- import torch
+    import torch
     max_seq_length = 2048 # Choose any! We auto support RoPE Scaling internally!
     dtype = None # None for auto detection. Float16 for Tesla T4, V100, Bfloat16 for Ampere+
     load_in_4bit = True # Use 4bit quantization to reduce memory usage. Can be False.
     from transformers import AutoTokenizer
-    ```
+  ```
+  ```
     model, tokenizer = FastLanguageModel.from_pretrained(
     model_name="DipeshChaudhary/ShareGPTChatBot-Counselchat1",  # Your fine-tuned model
     max_seq_length=max_seq_length,
     dtype=dtype,
     load_in_4bit=load_in_4bit,
     )
-    ``` -->
+  ```
+  ```
     #We now use the Llama-3 format for conversation style finetunes. We use Open Assistant conversations in ShareGPT style.
     **We use our get_chat_template function to get the correct chat template. They support zephyr, chatml, mistral, llama, alpaca, vicuna, vicuna_old and their own optimized unsloth template**
     from unsloth.chat_templates import get_chat_template
@@ -45,7 +47,7 @@ base_model: unsloth/llama-3-8b-Instruct-bnb-4bit
     chat_template = "llama-3", # Supports zephyr, chatml, mistral, llama, alpaca, vicuna, vicuna_old, unsloth
     mapping = {"role" : "from", "content" : "value", "user" : "human", "assistant" : "gpt"}, # ShareGPT style
     )
-    ```
+  ```
 
 # Uploaded  model