Update app.py

app.py

@@ -2,13 +2,10 @@ import torch
 from transformers import AutoTokenizer, AutoModelForCausalLM
 import gradio as gr
 
-model_id = "distilbert/distilgpt2"
-
-tokenizer = AutoTokenizer.from_pretrained(model_id)
-model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.float32)
-model.eval()
-
-def generate_text(prompt, temperature, top_k, top_p, max_tokens, repetition_penalty):
+def generate_text(model_id, prompt, temperature, top_k, top_p, max_tokens, repetition_penalty):
+    tokenizer = AutoTokenizer.from_pretrained(model_id)
+    model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.float32)
+    model.eval()
     inputs = tokenizer(prompt, return_tensors="pt")
     with torch.no_grad():
         output = model.generate(
@@ -26,6 +23,7 @@ def generate_text(prompt, temperature, top_k, top_p, max_tokens, repetition_pena
 gr.Interface(
     fn=generate_text,
     inputs=[
+        gr.Textbox(label="Model ID", placeholder="Enter Model ID"),
         gr.Textbox(label="Prompt", placeholder="Type something here...", lines=4),
         gr.Slider(0.1, 1.5, value=1.0, step=0.1, label="Temperature"),
         gr.Slider(1, 100, value=50, step=1, label="Top-K"),
@@ -34,6 +32,6 @@ gr.Interface(
         gr.Slider(0.5, 2.0, value=1.0, step=0.1, label="Repetition Penalty")
     ],
     outputs=gr.Textbox(label="Generated Text"),
-    title="🧠 AlphaMindQ Fork distilbert/distilgpt2",
+    title="🧠 AlphaMindQ Fork — Custom Hugging Face Model",
     theme="default"
 ).launch()