import gradio as gr from huggingface_hub import InferenceClient client = InferenceClient() def translate(prompt, max_tokens=256, temperature=0.3, top_p=0.9): output = client.text_generation( prompt, model="google/gemma-4-31B-it", max_new_tokens=max_tokens, temperature=temperature, top_p=top_p, ) return output demo = gr.Interface( fn=translate, inputs=[ gr.Textbox(label="Translation Prompt", placeholder="Translate to French: The weather is nice today.", lines=3), gr.Slider(minimum=64, maximum=1024, value=256, step=64, label="Max Tokens"), gr.Slider(minimum=0.1, maximum=1.0, value=0.3, step=0.05, label="Temperature"), gr.Slider(minimum=0.1, maximum=1.0, value=0.9, step=0.05, label="Top P"), ], outputs=gr.Textbox(label="Translation", lines=6), title="Adaption OPUS 100 Translation SFT 31B", description="LoRA adapter fine-tuned on 20K parallel translation pairs across 100 languages using Adaption's AutoScientist platform. Base model: Gemma 4 31B.", ) if __name__ == "__main__": demo.launch()