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import gradio as gr
import json
from transformers import pipeline
# Load Qwen2.5-3B (should fit in 16GB with CPU)
model_name = "Qwen/Qwen2.5-3B"
pipe = pipeline("text-generation", model=model_name, device=0)
# ✅ Load local GTA dataset (test set)
with open("gta_test.json", "r", encoding="utf-8") as f:
gta_data = json.load(f)
def run_model(input_text, use_gta_index):
if use_gta_index:
try:
index = int(input_text)
question = gta_data[index]["question"]
except Exception as e:
return f"❌ Invalid index: {e}"
else:
question = input_text
output = pipe(question, max_new_tokens=256, do_sample=True)
return f"**Question:** {question}\n\n**Response:**\n{output[0]['generated_text']}"
with gr.Blocks() as demo:
gr.Markdown("# 🤖 GTA Reasoning with Qwen2.5-3B")
gr.Markdown("Use a GTA query by index or enter your own.")
with gr.Row():
input_text = gr.Textbox(label="Enter a question or GTA index (0–228)")
use_index = gr.Checkbox(label="Treat input as GTA index", value=False)
run_btn = gr.Button("Generate")
output_md = gr.Markdown()
run_btn.click(run_model, inputs=[input_text, use_index], outputs=output_md)
demo.launch()
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