Update app.py

app.py

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+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import gradio as gr
+
+# Set Device to CPU
+device = torch.device('cpu')
+
+# Load the Models
+# Model 1: GPT-2 Medium
+tokenizer1 = AutoTokenizer.from_pretrained('gpt2-medium')
+model1 = AutoModelForCausalLM.from_pretrained('gpt2-medium')
+model1.to(device)
+
+# Model 2: GPT-Neo 125M
+tokenizer2 = AutoTokenizer.from_pretrained('EleutherAI/gpt-neo-125M')
+model2 = AutoModelForCausalLM.from_pretrained('EleutherAI/gpt-neo-125M')
+model2.to(device)
+
+# Define Text Generation Functions
+def generate_text_model1(prompt, temperature, top_p):
+    inputs = tokenizer1(prompt, return_tensors='pt').to(device)
+    with torch.no_grad():
+        outputs = model1.generate(
+            **inputs,
+            max_new_tokens=30,
+            do_sample=True,
+            top_k=50,
+            top_p=top_p,
+            temperature=temperature
+        )
+    text = tokenizer1.decode(outputs[0], skip_special_tokens=True)
+    return text
+
+def generate_text_model2(prompt, temperature, top_p):
+    inputs = tokenizer2(prompt, return_tensors='pt').to(device)
+    with torch.no_grad():
+        outputs = model2.generate(
+            **inputs,
+            max_new_tokens=30,
+            do_sample=True,
+            top_k=50,
+            top_p=top_p,
+            temperature=temperature
+        )
+    text = tokenizer2.decode(outputs[0], skip_special_tokens=True)
+    return text
+
+def compare_models(prompt, temperature, top_p):
+    output1 = generate_text_model1(prompt, temperature, top_p)
+    output2 = generate_text_model2(prompt, temperature, top_p)
+
+    # Include the parameter settings in the outputs
+    output1_with_params = f"**Temperature:** {temperature}, **Top-p:** {top_p}\n\n{output1}"
+    output2_with_params = f"**Temperature:** {temperature}, **Top-p:** {top_p}\n\n{output2}"
+
+    return output1_with_params, output2_with_params
+
+# Create Gradio Interface
+iface = gr.Interface(
+    fn=compare_models,
+    inputs=[
+        gr.Textbox(lines=2, placeholder='Enter a prompt here...', label='Prompt'),
+        gr.Slider(minimum=0.1, maximum=1.0, value=0.8, label='Temperature'),
+        gr.Slider(minimum=0.1, maximum=1.0, value=0.95, label='Top-p')
+    ],
+    outputs=[
+        gr.Markdown(label='GPT-2 Medium Output'),
+        gr.Markdown(label='GPT-Neo 125M Output')
+    ],
+    title='Compare Text Generation Models with Adjustable Parameters',
+    description='Enter a prompt and adjust the temperature and top-p parameters to see how they affect the generated text.'
+)
+
+if __name__ == "__main__":
+    iface.launch()