Spaces:
Runtime error
Runtime error
File size: 4,583 Bytes
8d6526d 4d64757 8d6526d cbca006 50f34cd cbca006 50f34cd cbca006 50f34cd 8d0ad90 50f34cd 8d6526d 4d64757 e06601a 6a693ac 0c10c32 4d64757 cfc4123 4d64757 e06601a 4d64757 8d6526d 4d64757 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 |
import os
import gradio as gr
import numpy as np
io1 = gr.Interface.load("huggingface/facebook/xm_transformer_s2ut_en-hk")
io2 = gr.Interface.load("huggingface/facebook/xm_transformer_s2ut_hk-en")
io3 = gr.Interface.load("huggingface/facebook/xm_transformer_unity_en-hk")
io4 = gr.Interface.load("huggingface/facebook/xm_transformer_unity_hk-en")
def inference(audio, model):
if model == "xm_transformer_s2ut_en-hk":
out_audio = io1(audio)
elif model == "xm_transformer_s2ut_hk-en":
out_audio = io2(audio)
elif model == "xm_transformer_unity_en-hk":
out_audio = io3(audio)
else:
out_audio = io4(audio)
return out_audio
css = """
.gradio-container {
font-family: 'IBM Plex Sans', sans-serif;
}
.gr-button {
color: black;
border-color: grey;
background: white;
}
input[type='range'] {
accent-color: black;
}
.dark input[type='range'] {
accent-color: #dfdfdf;
}
.container {
max-width: 730px;
margin: auto;
padding-top: 1.5rem;
}
.details:hover {
text-decoration: underline;
}
.gr-button {
white-space: nowrap;
}
.gr-button:focus {
border-color: rgb(147 197 253 / var(--tw-border-opacity));
outline: none;
box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000);
--tw-border-opacity: 1;
--tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color);
--tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color);
--tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity));
--tw-ring-opacity: .5;
}
.footer {
margin-bottom: 45px;
margin-top: 35px;
text-align: center;
border-bottom: 1px solid #e5e5e5;
}
.footer>p {
font-size: .8rem;
display: inline-block;
padding: 0 10px;
transform: translateY(10px);
background: white;
}
.dark .footer {
border-color: #303030;
}
.dark .footer>p {
background: #0b0f19;
}
.prompt h4{
margin: 1.25em 0 .25em 0;
font-weight: bold;
font-size: 115%;
}
.animate-spin {
animation: spin 1s linear infinite;
}
@keyframes spin {
from {
transform: rotate(0deg);
}
to {
transform: rotate(360deg);
}
}
"""
block = gr.Blocks(css=css)
with block:
gr.HTML(
"""
<div style="text-align: center; max-width: 700px; margin: 0 auto;">
<div
style="
display: inline-flex;
align-items: center;
gap: 0.8rem;
font-size: 1.75rem;
"
>
<h1 style="font-weight: 900; margin-bottom: 7px;">
Hokkien Translation
</h1>
</div>
<p style="margin-bottom: 10px; font-size: 94%">
A demo for fairseq speech-to-speech translation models. It supports S2UT and UnitY models for bidirectional Hokkien and English translation. Please select the model and record the input to submit.
</p>
</div>
"""
)
with gr.Group():
with gr.Box():
with gr.Row().style(mobile_collapse=False, equal_height=True):
audio = gr.Audio(
source="microphone", type="filepath", label="Input"
)
btn = gr.Button("Submit")
model = gr.Dropdown(choices=["xm_transformer_unity_en-hk", "xm_transformer_unity_hk-en", "xm_transformer_s2ut_en-hk", "xm_transformer_s2ut_hk-en"], value="xm_transformer_unity_en-hk",type="value", label="Model")
out = gr.Audio(label="Output")
btn.click(inference, inputs=[audio, model], outputs=out)
gr.HTML('''
<div class="footer">
<p>Model by <a href="https://ai.facebook.com/" style="text-decoration: underline;" target="_blank">Meta AI</a>
</p>
</div>
''')
block.launch() |