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| import gradio as gr | |
| from transformers import pipeline | |
| # Aapki exact Model ID yahan set kar di hai | |
| MODEL_ID = "Nebulixlabs/Nutral-Base" | |
| print("Loading model...") | |
| generator = pipeline("text-generation", model=MODEL_ID) | |
| print("Model loaded successfully!") | |
| def generate_text(prompt, max_length, temperature): | |
| results = generator( | |
| prompt, | |
| max_new_tokens=max_length, | |
| temperature=temperature, | |
| do_sample=True if temperature > 0 else False | |
| ) | |
| return results[0]['generated_text'] | |
| with gr.Blocks() as demo: | |
| gr.Markdown(f"# Nutral Base") | |
| with gr.Row(): | |
| with gr.Column(): | |
| input_text = gr.Textbox(lines=4, label="Input Prompt", placeholder="Type something here...") | |
| max_tokens = gr.Slider(minimum=10, maximum=512, value=100, step=10, label="Max New Tokens") | |
| temp = gr.Slider(minimum=0.1, maximum=1.0, value=0.7, step=0.1, label="Temperature") | |
| submit_btn = gr.Button("Generate") | |
| with gr.Column(): | |
| output_text = gr.Textbox(lines=6, label="Generated Text") | |
| submit_btn.click( | |
| fn=generate_text, | |
| inputs=[input_text, max_tokens, temp], | |
| outputs=output_text | |
| ) | |
| demo.launch() |