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on
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Running
on
T4
alan
commited on
Commit
•
6cd713c
1
Parent(s):
4dcbad1
update gradio
Browse files
README.md
CHANGED
@@ -4,7 +4,7 @@ emoji: 🔥
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colorFrom: yellow
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colorTo: blue
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sdk: gradio
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sdk_version:
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app_file: app.py
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pinned: false
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license: apache-2.0
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colorFrom: yellow
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colorTo: blue
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sdk: gradio
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sdk_version: 4.39.0
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app_file: app.py
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pinned: false
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license: apache-2.0
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app.py
CHANGED
@@ -4,6 +4,7 @@ import tempfile
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from math import floor
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from typing import Optional, List, Dict, Any
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import torch
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import gradio as gr
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import yt_dlp as youtube_dl
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@@ -26,6 +27,7 @@ else:
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torch_dtype = torch.float32
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device = "cpu"
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model_kwargs = {}
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# define the pipeline
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pipe = pipeline(
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model=MODEL_NAME,
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@@ -35,7 +37,7 @@ pipe = pipeline(
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device=device,
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model_kwargs=model_kwargs,
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trust_remote_code=True
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)
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def format_time(start: Optional[float], end: Optional[float]):
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@@ -53,6 +55,7 @@ def format_time(start: Optional[float], end: Optional[float]):
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return f"[{_format_time(start)}-> {_format_time(end)}]:"
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def get_prediction(inputs, prompt: Optional[str]):
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generate_kwargs = {"language": "japanese", "task": "transcribe"}
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if prompt:
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@@ -123,8 +126,8 @@ demo = gr.Blocks()
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mf_transcribe = gr.Interface(
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fn=transcribe,
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inputs=[
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gr.
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gr.
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],
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outputs=["text", "text"],
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layout="horizontal",
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@@ -137,8 +140,8 @@ mf_transcribe = gr.Interface(
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file_transcribe = gr.Interface(
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fn=transcribe,
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inputs=[
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gr.
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gr.
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],
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outputs=["text", "text"],
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layout="horizontal",
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@@ -150,8 +153,8 @@ file_transcribe = gr.Interface(
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yt_transcribe = gr.Interface(
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fn=yt_transcribe,
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inputs=[
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gr.
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gr.
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],
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outputs=["html", "text", "text"],
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layout="horizontal",
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from math import floor
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from typing import Optional, List, Dict, Any
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import spaces
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import torch
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import gradio as gr
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import yt_dlp as youtube_dl
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torch_dtype = torch.float32
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device = "cpu"
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model_kwargs = {}
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print(device)
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# define the pipeline
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pipe = pipeline(
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model=MODEL_NAME,
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device=device,
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model_kwargs=model_kwargs,
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trust_remote_code=True
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).to(device)
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def format_time(start: Optional[float], end: Optional[float]):
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return f"[{_format_time(start)}-> {_format_time(end)}]:"
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@spaces.GPU
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def get_prediction(inputs, prompt: Optional[str]):
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generate_kwargs = {"language": "japanese", "task": "transcribe"}
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if prompt:
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mf_transcribe = gr.Interface(
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fn=transcribe,
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inputs=[
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gr.Audio(sources="microphone", type="filepath", optional=True),
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gr.Textbox(lines=1, placeholder="Prompt", optional=True),
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],
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outputs=["text", "text"],
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layout="horizontal",
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file_transcribe = gr.Interface(
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fn=transcribe,
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inputs=[
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gr.Audio(sources="upload", type="filepath", optional=True, label="Audio file"),
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gr.Textbox(lines=1, placeholder="Prompt", optional=True),
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],
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outputs=["text", "text"],
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layout="horizontal",
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yt_transcribe = gr.Interface(
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fn=yt_transcribe,
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inputs=[
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gr.Textbox(lines=1, placeholder="Paste the URL to a YouTube video here", label="YouTube URL"),
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gr.Textbox(lines=1, placeholder="Prompt", optional=True),
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],
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outputs=["html", "text", "text"],
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layout="horizontal",
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