| import gradio as gr | |
| from transformers import pipeline | |
| # Pretrained model load karo (direct original repo se) | |
| model_name = "ByteDance-Seed/UI-TARS-1.5-7B" # ← Replace karo actual model path se | |
| generator = pipeline("text-generation", model=model_name) | |
| # Text generate karne ka function | |
| def generate_text(prompt): | |
| result = generator(prompt, max_new_tokens=100, do_sample=True) | |
| return result[0]["generated_text"] | |
| # Gradio Interface | |
| gr.Interface( | |
| fn=generate_text, | |
| inputs=gr.Textbox(lines=2, placeholder="Enter your prompt..."), | |
| outputs="text", | |
| title="UITARS 1.5 Text Generator" | |
| ).launch() | |