Update README.md

README.md

@@ -31,23 +31,17 @@ The model contains three versions:
 # Model Deployment for Private Gene Set Analysis
 
 ```python
-  from transformers import logging
+  import transformers
+  from transformers import AutoTokenizer, AutoModelForCausalLM
   
-  logging.set_verbosity_error()
-  import re
-  import torch
-  import openai
-  import numpy as np
-  import pandas as pd
-  
-  from scipy import stats
-  from rouge_score import rouge_scorer
-  from torch import Tensor
-  import tqdm
-  
-  tokenizer_test = AutoTokenizer.from_pretrained(model_path, token = 'xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx') # Your access key of hugging face
+  tokenizer_test = AutoTokenizer.from_pretrained(
+      model_path,
+      token = 'xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx'  # Your access key of hugging face
+  ) 
   model_test = AutoModelForCausalLM.from_pretrained(
-      model_path, device_map='auto', token = 'xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx'  # Your access key of hugging face
+      model_path,
+      device_map='auto',
+      token = 'xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx'  # Your access key of hugging face
   )
   
   def complete_chat(system, prompt, model, tokenizer):
@@ -73,13 +67,12 @@ The model contains three versions:
 
   def llama(genes):    
       genes = genes.replace("/",",").replace(" ",",")
-      
       prompt = users(genes)
       summary =complete_chat(system, prompt, model_test, tokenizer_test)
       return summary
 
   if __name__ == "__main__":
-    genes = "Your Gene Set Separated by comma (,)"
+    genes = "Your Gene Set Separated by comma (,)!"
     result = llama(genes)
     print(result)
 ```