Delete app.py

app.py

@@ -1,45 +0,0 @@
-import gradio as gr
-import torch
-from transformers import AutoTokenizer, AutoModelForCausalLM
-
-tokenizer = AutoTokenizer.from_pretrained("HooshvareLab/gpt2-fa", use_fast=True)
-model = AutoModelForCausalLM.from_pretrained(
-    "HooshvareLab/gpt2-fa",
-    torch_dtype=torch.bfloat16
-).to("cpu")
-
-CONTEXT = (
-    "This is a conversation with ParvizGPT. It is an artificial intelligence model designed by Amir Mahdi Parviz, "
-    "an NLP expert, to help you with various tasks such as answering questions, "
-    "providing recommendations, and assisting with decision-making. Ask it anything!"
-)
-pretokenized_context = tokenizer(CONTEXT, return_tensors="pt").input_ids.to("cpu")
-
-def generate_response(message, chat_history):
-    prompt = torch.cat(
-        [pretokenized_context, tokenizer("\nYou: " + message + "\nParvizGPT: ", return_tensors="pt").input_ids.to("cpu")],
-        dim=1
-    )
-
-    with torch.no_grad():
-        outputs = model.generate(
-            prompt,
-            max_new_tokens=32,
-            temperature=0.6,
-            top_k=20,
-            top_p=0.8,
-            do_sample=True
-        )
-
-    result = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    response = result.split("ParvizGPT:")[-1].strip()
-    return chat_history + [(message, response)]
-
-with gr.Blocks() as demo:
-    gr.Markdown("<h1 style='text-align: center;'>💬 Parviz GPT</h1>")
-    chatbot = gr.Chatbot(label="Response")
-    msg = gr.Textbox(label="Input", placeholder="Ask your question...", lines=1)
-    msg.submit(generate_response, [msg, chatbot], chatbot)
-    gr.ClearButton([msg, chatbot])
-
-demo.launch()