| import gradio as gr | |
| from transformers import pipeline | |
| pipeline = pipeline(task="text-generation", model="bigscience/bloom-350m") | |
| def translate(text): | |
| predictions = pipeline(text) | |
| return {p["label"]: p["score"] for p in predictions} | |
| gr.Interface( | |
| predict, | |
| inputs=gr.inputs.Text(label="text", type="filepath"), | |
| outputs=gr.outputs.Label(num_top_classes=2), | |
| title="Middle Earth Tales", | |
| ).launch() |