Update README.md

README.md

@@ -44,62 +44,6 @@ Refer to [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) model card fo
 
 [GPTQ format](https://github.com/STEM-ai/Phi-2/blob/ab1ced8d7922765344d824acf1924df99606b4fc/chat-GPTQ.py)
 
-### How to use
-```python
-import torch
-from peft import PeftModel, PeftConfig
-from transformers import AutoModelForCausalLM, AutoTokenizer
-import warnings
-import os
-
-os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
-warnings.filterwarnings("ignore", category=UserWarning, module='transformers.generation.utils')
-
-def load_model_and_tokenizer():
-    base_model = "microsoft/phi-2"
-    peft_model_id = "STEM-AI-mtl/phi-2-electrical-engineering"
-    config = PeftConfig.from_pretrained(peft_model_id, trust_remote_code=True)
-    model = AutoModelForCausalLM.from_pretrained(base_model, device_map="cuda:0",return_dict=True, trust_remote_code=True)
-
-    model = model.to('cuda')
-
-    tokenizer = AutoTokenizer.from_pretrained(base_model)
-    model = PeftModel.from_pretrained(model, peft_model_id, trust_remote_code=True)
-
-    model = model.to('cuda')
-
-    return model, tokenizer
-
-def generate(instruction, model, tokenizer):                              
-    inputs = tokenizer(instruction, return_tensors="pt", return_attention_mask=False)
-    inputs = inputs.to('cuda')
-    outputs = model.generate(
-        **inputs, 
-        max_length=350,
-        do_sample=True, 
-        temperature=0.7,
-        top_k=50,  
-        top_p=0.9,
-        repetition_penalty=1,
-    )
-    text = tokenizer.batch_decode(outputs)[0]
-    return text
-
-
-if __name__ == '__main__':
-    model, tokenizer = load_model_and_tokenizer()
-    while True:  
-        instruction = input("Enter your instruction: ")
-        if not instruction:
-            continue   
-        if instruction.lower() in ["exit", "quit", "exit()", "quit()"]:
-            print("Exiting...")
-            break 
-
-        answer = generate(instruction, model, tokenizer)
-        print(f'Answer: {answer}')
-```
-
 ## Training Details
 
 ### Training Data