Update app.py

app.py

@@ -1,5 +1,5 @@
 import subprocess
-subprocess.run(["pip", "install", "gradio", "torch", "transformers"])
+subprocess.run(["pip", "install","gradio","torch","transformers"])
 import re
 import gradio as gr
 import torch
@@ -13,13 +13,15 @@ device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 # Define a function for generating text based on a prompt using the fine-tuned GPT-2 model and the tokenizer
 def generate_text(prompt, length=100, theme=None, **kwargs):
 
-    model_name = "https://huggingface.co/spaces/sailormars18/Yelp-reviews-usingGPT2/tree/main"
+    model_url = "https://huggingface.co/spaces/sailormars18/Yelp-reviews-usingGPT2/blob/main/pytorch_model.bin"
+    config_url = "https://huggingface.co/spaces/sailormars18/Yelp-reviews-usingGPT2/blob/main/config.json"
+    generation_config_url = "https://huggingface.co/spaces/sailormars18/Yelp-reviews-usingGPT2/blob/main/generation_config.json"
     
     # Load the model from the Hugging Face space
-    model = GPT2LMHeadModel.from_pretrained(model_name).to(device)
+    model = transformers.GPT2LMHeadModel.from_pretrained(model_url, config=config_url).to(device)
     
     # Load the tokenizer from the Hugging Face space
-    tokenizer = GPT2Tokenizer.from_pretrained(model_name)
+    tokenizer = transformers.GPT2Tokenizer.from_pretrained('gpt2')
 
     # If a theme is specified, add it to the prompt as a prefix for a special token
     if theme:
@@ -65,7 +67,7 @@ def generate_text(prompt, length=100, theme=None, **kwargs):
 iface = gr.Interface(
     fn=generate_text,
     inputs=[
-        gr.inputs.Textbox(label="Prompt"),
+        "text", 
         gr.inputs.Slider(minimum=10, maximum=100, default=50, label='Length of text'),
         gr.inputs.Textbox(default='Food', label='Theme')
     ],