| <html> | |
| <head> | |
| <script type="module" crossorigin src="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.js"></script> | |
| <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.css" /> | |
| </head> | |
| <body> | |
| <gradio-lite> | |
| <gradio-requirements> | |
| transformers_js_py | |
| </gradio-requirements> | |
| <gradio-file name="app.py" entrypoint> | |
| from transformers_js import import_transformers_js | |
| import gradio as gr | |
| speaker_embeddings = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/speaker_embeddings.bin'; | |
| transformers = await import_transformers_js() | |
| pipeline = transformers.pipeline | |
| synthesizer = await pipeline('text-to-speech', 'Xenova/speecht5_tts', { "quantized": False }) | |
| async def classify(text): | |
| return await synthesizer(text, { "speaker_embeddings": speaker_embeddings }); | |
| demo = gr.Interface(classify, "textbox", "audio") | |
| demo.launch() | |
| </gradio-file> | |
| </gradio-lite> | |
| </body> | |
| </html> | |