Spaces:
Running
Running
Update app.py
Browse files
app.py
CHANGED
@@ -1,20 +1,185 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
import torch
|
2 |
|
3 |
import gradio as gr
|
4 |
import yt_dlp as youtube_dl
|
5 |
-
|
6 |
from transformers import pipeline
|
7 |
-
from
|
8 |
-
|
9 |
import tempfile
|
10 |
import os
|
11 |
|
12 |
MODEL_NAME = "razhan/whisper-small-ckb"
|
13 |
BATCH_SIZE = 1
|
14 |
FILE_LIMIT_MB = 10
|
15 |
-
YT_LENGTH_LIMIT_S = 60 * 10
|
16 |
|
17 |
device = 0 if torch.cuda.is_available() else "cpu"
|
|
|
18 |
pipe = pipeline(
|
19 |
task="automatic-speech-recognition",
|
20 |
model=MODEL_NAME,
|
@@ -22,71 +187,27 @@ pipe = pipeline(
|
|
22 |
device=device,
|
23 |
)
|
24 |
|
25 |
-
pipe.model.config.forced_decoder_ids = pipe.tokenizer.get_decoder_prompt_ids(task="transcribe")
|
26 |
|
27 |
-
|
28 |
-
|
29 |
-
if
|
30 |
-
|
31 |
-
"WARNING: You've uploaded an audio file and used the microphone. "
|
32 |
-
"The recorded file from the microphone will be used and the uploaded audio will be discarded.\n"
|
33 |
-
)
|
34 |
|
35 |
-
|
36 |
-
|
37 |
-
|
38 |
-
file = microphone if microphone is not None else file_upload
|
39 |
-
|
40 |
-
text = pipe(file)["text"]
|
41 |
-
|
42 |
-
return warn_output + text
|
43 |
|
44 |
|
45 |
def _return_yt_html_embed(yt_url):
|
46 |
-
|
47 |
-
video_id = yt_url.split('/')[-1].split('?')[0]
|
48 |
-
else:
|
49 |
-
video_id = yt_url.split("?v=")[-1].split('&')[0]
|
50 |
-
|
51 |
HTML_str = (
|
52 |
-
f'<center
|
53 |
-
|
54 |
-
'allowfullscreen></iframe></center>'
|
55 |
)
|
56 |
return HTML_str
|
57 |
|
58 |
-
|
59 |
-
|
60 |
-
|
61 |
-
|
62 |
-
def yt_transcribe(yt_url, task="transcribe", max_filesize=75.0, progress=gr.Progress()):
|
63 |
-
html_embed_str = _return_yt_html_embed(yt_url)
|
64 |
-
|
65 |
-
with tempfile.TemporaryDirectory() as tmpdirname:
|
66 |
-
filepath = os.path.join(tmpdirname, "video.mp4")
|
67 |
-
download_yt_audio(yt_url, filepath)
|
68 |
-
with open(filepath, "rb") as f:
|
69 |
-
inputs = f.read()
|
70 |
-
|
71 |
-
inputs = ffmpeg_read(inputs, pipe.feature_extractor.sampling_rate)
|
72 |
-
inputs = {"array": inputs, "sampling_rate": pipe.feature_extractor.sampling_rate}
|
73 |
-
|
74 |
-
|
75 |
-
|
76 |
-
start_time = time.time()
|
77 |
-
outputs = pipe(inputs, chunk_length_s=30, batch_size=BATCH_SIZE, generate_kwargs={"task": task, "language": "persian"}, return_timestamps=False)
|
78 |
-
exec_time = time.time() - start_time
|
79 |
-
logging.info(print(f"transcribe: {exec_time} sec."))
|
80 |
-
|
81 |
-
return html_embed_str, txt, exec_time
|
82 |
-
|
83 |
-
|
84 |
-
def download_yt_audio(yt_url, filename, progress=gr.Progress()):
|
85 |
-
if '&list' in yt_url:
|
86 |
-
yt_url = yt_url.split('&list')[0]
|
87 |
-
|
88 |
info_loader = youtube_dl.YoutubeDL()
|
89 |
-
|
90 |
try:
|
91 |
info = info_loader.extract_info(yt_url, download=False)
|
92 |
except youtube_dl.utils.DownloadError as err:
|
@@ -107,27 +228,60 @@ def download_yt_audio(yt_url, filename, progress=gr.Progress()):
|
|
107 |
file_length_hms = time.strftime("%HH:%MM:%SS", time.gmtime(file_length_s))
|
108 |
raise gr.Error(f"Maximum YouTube length is {yt_length_limit_hms}, got {file_length_hms} YouTube video.")
|
109 |
|
110 |
-
|
111 |
-
ydl_opts = {"outtmpl": filename, "format": "bestaudio/best"}
|
112 |
|
113 |
with youtube_dl.YoutubeDL(ydl_opts) as ydl:
|
114 |
try:
|
115 |
ydl.download([yt_url])
|
116 |
except youtube_dl.utils.ExtractorError as err:
|
117 |
raise gr.Error(str(err))
|
118 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
119 |
|
120 |
|
|
|
|
|
121 |
mf_transcribe = gr.Interface(
|
122 |
fn=transcribe,
|
123 |
inputs=[
|
124 |
gr.Audio(sources="microphone", type="filepath"),
|
125 |
-
gr.
|
126 |
],
|
127 |
outputs="text",
|
128 |
title="Whisper Central Kurdish (Sorani) Demo: Transcribe Audio",
|
129 |
description=(
|
130 |
-
"Transcribe long-form microphone or audio inputs with the click of a button! Demo uses the
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
131 |
f" checkpoint [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe audio files"
|
132 |
" of arbitrary length."
|
133 |
),
|
@@ -136,27 +290,21 @@ mf_transcribe = gr.Interface(
|
|
136 |
|
137 |
yt_transcribe = gr.Interface(
|
138 |
fn=yt_transcribe,
|
139 |
-
inputs=[
|
140 |
-
|
141 |
-
gr.
|
142 |
-
|
143 |
-
|
144 |
-
show_copy_button=True,
|
145 |
-
),
|
146 |
-
gr.Text(label="Transcription Time")
|
147 |
-
],
|
148 |
title="Whisper Central Kurdish (Sorani) Demo: Transcribe YouTube",
|
149 |
description=(
|
150 |
-
"Transcribe long-form YouTube videos with the click of a button! Demo uses the
|
151 |
-
f" [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe
|
152 |
" arbitrary length."
|
153 |
),
|
154 |
allow_flagging="never",
|
155 |
)
|
156 |
|
|
|
|
|
157 |
|
158 |
-
demo
|
159 |
-
|
160 |
-
if __name__ == "__main__":
|
161 |
-
demo.launch()
|
162 |
-
|
|
|
1 |
+
# import torch
|
2 |
+
|
3 |
+
# import gradio as gr
|
4 |
+
# import yt_dlp as youtube_dl
|
5 |
+
|
6 |
+
# from transformers import pipeline
|
7 |
+
# from huggingface_hub import model_info
|
8 |
+
# import re
|
9 |
+
# import tempfile
|
10 |
+
# import os
|
11 |
+
|
12 |
+
# MODEL_NAME = "razhan/whisper-small-ckb"
|
13 |
+
# BATCH_SIZE = 1
|
14 |
+
# FILE_LIMIT_MB = 10
|
15 |
+
# YT_LENGTH_LIMIT_S = 60 * 10
|
16 |
+
|
17 |
+
# device = 0 if torch.cuda.is_available() else "cpu"
|
18 |
+
# pipe = pipeline(
|
19 |
+
# task="automatic-speech-recognition",
|
20 |
+
# model=MODEL_NAME,
|
21 |
+
# chunk_length_s=30,
|
22 |
+
# device=device,
|
23 |
+
# )
|
24 |
+
|
25 |
+
# pipe.model.config.forced_decoder_ids = pipe.tokenizer.get_decoder_prompt_ids(task="transcribe")
|
26 |
+
|
27 |
+
# def transcribe(microphone, file_upload):
|
28 |
+
# warn_output = ""
|
29 |
+
# if (microphone is not None) and (file_upload is not None):
|
30 |
+
# warn_output = (
|
31 |
+
# "WARNING: You've uploaded an audio file and used the microphone. "
|
32 |
+
# "The recorded file from the microphone will be used and the uploaded audio will be discarded.\n"
|
33 |
+
# )
|
34 |
+
|
35 |
+
# elif (microphone is None) and (file_upload is None):
|
36 |
+
# return "ERROR: You have to either use the microphone or upload an audio file"
|
37 |
+
|
38 |
+
# file = microphone if microphone is not None else file_upload
|
39 |
+
|
40 |
+
# text = pipe(file)["text"]
|
41 |
+
|
42 |
+
# return warn_output + text
|
43 |
+
|
44 |
+
|
45 |
+
# def _return_yt_html_embed(yt_url):
|
46 |
+
# if 'youtu.be' in yt_url:
|
47 |
+
# video_id = yt_url.split('/')[-1].split('?')[0]
|
48 |
+
# else:
|
49 |
+
# video_id = yt_url.split("?v=")[-1].split('&')[0]
|
50 |
+
|
51 |
+
# HTML_str = (
|
52 |
+
# f'<center><iframe width="560" height="315" src="https://www.youtube.com/embed/{video_id}" '
|
53 |
+
# 'frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" '
|
54 |
+
# 'allowfullscreen></iframe></center>'
|
55 |
+
# )
|
56 |
+
# return HTML_str
|
57 |
+
|
58 |
+
|
59 |
+
|
60 |
+
|
61 |
+
|
62 |
+
# def yt_transcribe(yt_url, task="transcribe", max_filesize=75.0, progress=gr.Progress()):
|
63 |
+
# html_embed_str = _return_yt_html_embed(yt_url)
|
64 |
+
|
65 |
+
# with tempfile.TemporaryDirectory() as tmpdirname:
|
66 |
+
# filepath = os.path.join(tmpdirname, "video.mp4")
|
67 |
+
# download_yt_audio(yt_url, filepath)
|
68 |
+
# with open(filepath, "rb") as f:
|
69 |
+
# inputs = f.read()
|
70 |
+
|
71 |
+
# inputs = ffmpeg_read(inputs, pipe.feature_extractor.sampling_rate)
|
72 |
+
# inputs = {"array": inputs, "sampling_rate": pipe.feature_extractor.sampling_rate}
|
73 |
+
|
74 |
+
|
75 |
+
|
76 |
+
# start_time = time.time()
|
77 |
+
# outputs = pipe(inputs, chunk_length_s=30, batch_size=BATCH_SIZE, generate_kwargs={"task": task, "language": "persian"}, return_timestamps=False)
|
78 |
+
# exec_time = time.time() - start_time
|
79 |
+
# logging.info(print(f"transcribe: {exec_time} sec."))
|
80 |
+
|
81 |
+
# return html_embed_str, txt, exec_time
|
82 |
+
|
83 |
+
|
84 |
+
# def download_yt_audio(yt_url, filename, progress=gr.Progress()):
|
85 |
+
# if '&list' in yt_url:
|
86 |
+
# yt_url = yt_url.split('&list')[0]
|
87 |
+
|
88 |
+
# info_loader = youtube_dl.YoutubeDL()
|
89 |
+
|
90 |
+
# try:
|
91 |
+
# info = info_loader.extract_info(yt_url, download=False)
|
92 |
+
# except youtube_dl.utils.DownloadError as err:
|
93 |
+
# raise gr.Error(str(err))
|
94 |
+
|
95 |
+
# file_length = info["duration_string"]
|
96 |
+
# file_h_m_s = file_length.split(":")
|
97 |
+
# file_h_m_s = [int(sub_length) for sub_length in file_h_m_s]
|
98 |
+
|
99 |
+
# if len(file_h_m_s) == 1:
|
100 |
+
# file_h_m_s.insert(0, 0)
|
101 |
+
# if len(file_h_m_s) == 2:
|
102 |
+
# file_h_m_s.insert(0, 0)
|
103 |
+
# file_length_s = file_h_m_s[0] * 3600 + file_h_m_s[1] * 60 + file_h_m_s[2]
|
104 |
+
|
105 |
+
# if file_length_s > YT_LENGTH_LIMIT_S:
|
106 |
+
# yt_length_limit_hms = time.strftime("%HH:%MM:%SS", time.gmtime(YT_LENGTH_LIMIT_S))
|
107 |
+
# file_length_hms = time.strftime("%HH:%MM:%SS", time.gmtime(file_length_s))
|
108 |
+
# raise gr.Error(f"Maximum YouTube length is {yt_length_limit_hms}, got {file_length_hms} YouTube video.")
|
109 |
+
|
110 |
+
# # ydl_opts = {"outtmpl": filename, "format": "worstvideo[ext=mp4]+bestaudio[ext=m4a]/best[ext=mp4]/best"}
|
111 |
+
# ydl_opts = {"outtmpl": filename, "format": "bestaudio/best"}
|
112 |
+
|
113 |
+
# with youtube_dl.YoutubeDL(ydl_opts) as ydl:
|
114 |
+
# try:
|
115 |
+
# ydl.download([yt_url])
|
116 |
+
# except youtube_dl.utils.ExtractorError as err:
|
117 |
+
# raise gr.Error(str(err))
|
118 |
+
# progress(1, desc="Video downloaded from YouTube!")
|
119 |
+
|
120 |
+
|
121 |
+
# mf_transcribe = gr.Interface(
|
122 |
+
# fn=transcribe,
|
123 |
+
# inputs=[
|
124 |
+
# gr.Audio(sources="microphone", type="filepath"),
|
125 |
+
# gr.Audio(sources="upload", type="filepath"),
|
126 |
+
# ],
|
127 |
+
# outputs="text",
|
128 |
+
# title="Whisper Central Kurdish (Sorani) Demo: Transcribe Audio",
|
129 |
+
# description=(
|
130 |
+
# "Transcribe long-form microphone or audio inputs with the click of a button! Demo uses the the fine-tuned"
|
131 |
+
# f" checkpoint [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe audio files"
|
132 |
+
# " of arbitrary length."
|
133 |
+
# ),
|
134 |
+
# allow_flagging="never",
|
135 |
+
# )
|
136 |
+
|
137 |
+
# yt_transcribe = gr.Interface(
|
138 |
+
# fn=yt_transcribe,
|
139 |
+
# inputs=[gr.Textbox(lines=1, placeholder="Paste the URL to a YouTube video here", label="YouTube URL")],
|
140 |
+
# outputs=["html",
|
141 |
+
# gr.Textbox(
|
142 |
+
# label="Output",
|
143 |
+
# rtl=True,
|
144 |
+
# show_copy_button=True,
|
145 |
+
# ),
|
146 |
+
# gr.Text(label="Transcription Time")
|
147 |
+
# ],
|
148 |
+
# title="Whisper Central Kurdish (Sorani) Demo: Transcribe YouTube",
|
149 |
+
# description=(
|
150 |
+
# "Transcribe long-form YouTube videos with the click of a button! Demo uses the the fine-tuned checkpoint:"
|
151 |
+
# f" [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe audio files of"
|
152 |
+
# " arbitrary length."
|
153 |
+
# ),
|
154 |
+
# allow_flagging="never",
|
155 |
+
# )
|
156 |
+
|
157 |
+
|
158 |
+
# demo = gr.TabbedInterface([mf_transcribe, yt_transcribe], ["Transcribe Audio", "Transcribe YouTube"])
|
159 |
+
|
160 |
+
# if __name__ == "__main__":
|
161 |
+
# demo.launch()
|
162 |
+
|
163 |
+
|
164 |
+
|
165 |
+
import spaces
|
166 |
import torch
|
167 |
|
168 |
import gradio as gr
|
169 |
import yt_dlp as youtube_dl
|
|
|
170 |
from transformers import pipeline
|
171 |
+
from transformers.pipelines.audio_utils import ffmpeg_read
|
172 |
+
|
173 |
import tempfile
|
174 |
import os
|
175 |
|
176 |
MODEL_NAME = "razhan/whisper-small-ckb"
|
177 |
BATCH_SIZE = 1
|
178 |
FILE_LIMIT_MB = 10
|
179 |
+
YT_LENGTH_LIMIT_S = 60 * 10 # limit to 1 hour YouTube files
|
180 |
|
181 |
device = 0 if torch.cuda.is_available() else "cpu"
|
182 |
+
|
183 |
pipe = pipeline(
|
184 |
task="automatic-speech-recognition",
|
185 |
model=MODEL_NAME,
|
|
|
187 |
device=device,
|
188 |
)
|
189 |
|
|
|
190 |
|
191 |
+
@spaces.GPU
|
192 |
+
def transcribe(inputs, task):
|
193 |
+
if inputs is None:
|
194 |
+
raise gr.Error("No audio file submitted! Please upload or record an audio file before submitting your request.")
|
|
|
|
|
|
|
195 |
|
196 |
+
text = pipe(inputs, batch_size=BATCH_SIZE, generate_kwargs={"task": task}, return_timestamps=True)["text"]
|
197 |
+
return text
|
|
|
|
|
|
|
|
|
|
|
|
|
198 |
|
199 |
|
200 |
def _return_yt_html_embed(yt_url):
|
201 |
+
video_id = yt_url.split("?v=")[-1]
|
|
|
|
|
|
|
|
|
202 |
HTML_str = (
|
203 |
+
f'<center> <iframe width="500" height="320" src="https://www.youtube.com/embed/{video_id}"> </iframe>'
|
204 |
+
" </center>"
|
|
|
205 |
)
|
206 |
return HTML_str
|
207 |
|
208 |
+
def download_yt_audio(yt_url, filename):
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
209 |
info_loader = youtube_dl.YoutubeDL()
|
210 |
+
|
211 |
try:
|
212 |
info = info_loader.extract_info(yt_url, download=False)
|
213 |
except youtube_dl.utils.DownloadError as err:
|
|
|
228 |
file_length_hms = time.strftime("%HH:%MM:%SS", time.gmtime(file_length_s))
|
229 |
raise gr.Error(f"Maximum YouTube length is {yt_length_limit_hms}, got {file_length_hms} YouTube video.")
|
230 |
|
231 |
+
ydl_opts = {"outtmpl": filename, "format": "worstvideo[ext=mp4]+bestaudio[ext=m4a]/best[ext=mp4]/best"}
|
|
|
232 |
|
233 |
with youtube_dl.YoutubeDL(ydl_opts) as ydl:
|
234 |
try:
|
235 |
ydl.download([yt_url])
|
236 |
except youtube_dl.utils.ExtractorError as err:
|
237 |
raise gr.Error(str(err))
|
238 |
+
|
239 |
+
@spaces.GPU
|
240 |
+
def yt_transcribe(yt_url, task, max_filesize=75.0):
|
241 |
+
html_embed_str = _return_yt_html_embed(yt_url)
|
242 |
+
|
243 |
+
with tempfile.TemporaryDirectory() as tmpdirname:
|
244 |
+
filepath = os.path.join(tmpdirname, "video.mp4")
|
245 |
+
download_yt_audio(yt_url, filepath)
|
246 |
+
with open(filepath, "rb") as f:
|
247 |
+
inputs = f.read()
|
248 |
+
|
249 |
+
inputs = ffmpeg_read(inputs, pipe.feature_extractor.sampling_rate)
|
250 |
+
inputs = {"array": inputs, "sampling_rate": pipe.feature_extractor.sampling_rate}
|
251 |
+
|
252 |
+
text = pipe(inputs, batch_size=BATCH_SIZE, generate_kwargs={"task": task}, return_timestamps=True)["text"]
|
253 |
+
|
254 |
+
return html_embed_str, text
|
255 |
|
256 |
|
257 |
+
demo = gr.Blocks(theme=gr.themes.Ocean())
|
258 |
+
|
259 |
mf_transcribe = gr.Interface(
|
260 |
fn=transcribe,
|
261 |
inputs=[
|
262 |
gr.Audio(sources="microphone", type="filepath"),
|
263 |
+
gr.Radio(["transcribe", "translate"], label="Task", value="transcribe"),
|
264 |
],
|
265 |
outputs="text",
|
266 |
title="Whisper Central Kurdish (Sorani) Demo: Transcribe Audio",
|
267 |
description=(
|
268 |
+
"Transcribe long-form microphone or audio inputs with the click of a button! Demo uses the"
|
269 |
+
f" checkpoint [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe audio files"
|
270 |
+
" of arbitrary length."
|
271 |
+
),
|
272 |
+
allow_flagging="never",
|
273 |
+
)
|
274 |
+
|
275 |
+
file_transcribe = gr.Interface(
|
276 |
+
fn=transcribe,
|
277 |
+
inputs=[
|
278 |
+
gr.Audio(sources="upload", type="filepath", label="Audio file"),
|
279 |
+
gr.Radio(["transcribe", "translate"], label="Task", value="transcribe"),
|
280 |
+
],
|
281 |
+
outputs="text",
|
282 |
+
title="Whisper Central Kurdish (Sorani) Demo: Transcribe Audio",
|
283 |
+
description=(
|
284 |
+
"Transcribe long-form microphone or audio inputs with the click of a button! Demo uses the"
|
285 |
f" checkpoint [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe audio files"
|
286 |
" of arbitrary length."
|
287 |
),
|
|
|
290 |
|
291 |
yt_transcribe = gr.Interface(
|
292 |
fn=yt_transcribe,
|
293 |
+
inputs=[
|
294 |
+
gr.Textbox(lines=1, placeholder="Paste the URL to a YouTube video here", label="YouTube URL"),
|
295 |
+
gr.Radio(["transcribe", "translate"], label="Task", value="transcribe")
|
296 |
+
],
|
297 |
+
outputs=["html", "text"],
|
|
|
|
|
|
|
|
|
298 |
title="Whisper Central Kurdish (Sorani) Demo: Transcribe YouTube",
|
299 |
description=(
|
300 |
+
"Transcribe long-form YouTube videos with the click of a button! Demo uses the checkpoint"
|
301 |
+
f" [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe video files of"
|
302 |
" arbitrary length."
|
303 |
),
|
304 |
allow_flagging="never",
|
305 |
)
|
306 |
|
307 |
+
with demo:
|
308 |
+
gr.TabbedInterface([mf_transcribe, file_transcribe, yt_transcribe], ["Microphone", "Audio file", "YouTube"])
|
309 |
|
310 |
+
demo.queue().launch(ssr_mode=False)
|
|
|
|
|
|
|
|