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#!/usr/bin/env python | |
from __future__ import annotations | |
import os | |
import gradio as gr | |
from inference import InferencePipeline | |
class InferenceUtil: | |
def __init__(self, hf_token: str | None): | |
self.hf_token = hf_token | |
def load_model_info(self, model_id: str) -> tuple[str, str]: | |
try: | |
card = InferencePipeline.get_model_card(model_id, self.hf_token) | |
except Exception: | |
return '', '' | |
base_model = getattr(card.data, 'base_model', '') | |
training_prompt = getattr(card.data, 'training_prompt', '') | |
return base_model, training_prompt | |
TITLE = '# [Tune-A-Video](https://tuneavideo.github.io/)' | |
HF_TOKEN = os.getenv('HF_TOKEN') | |
pipe = InferencePipeline(HF_TOKEN) | |
app = InferenceUtil(HF_TOKEN) | |
with gr.Blocks(css='style.css') as demo: | |
gr.Markdown(TITLE) | |
with gr.Row(): | |
with gr.Column(): | |
with gr.Box(): | |
model_id = gr.Dropdown( | |
label='Model ID', | |
choices=[ | |
'Tune-A-Video-library/a-man-is-surfing', | |
'Tune-A-Video-library/mo-di-bear-guitar', | |
'Tune-A-Video-library/redshift-man-skiing', | |
], | |
value='Tune-A-Video-library/a-man-is-surfing') | |
with gr.Accordion( | |
label= | |
'Model info (Base model and prompt used for training)', | |
open=False): | |
with gr.Row(): | |
base_model_used_for_training = gr.Text( | |
label='Base model', interactive=False) | |
prompt_used_for_training = gr.Text( | |
label='Training prompt', interactive=False) | |
prompt = gr.Textbox(label='Prompt', | |
max_lines=1, | |
placeholder='Example: "A panda is surfing"') | |
video_length = gr.Slider(label='Video length', | |
minimum=4, | |
maximum=12, | |
step=1, | |
value=8) | |
fps = gr.Slider(label='FPS', | |
minimum=1, | |
maximum=12, | |
step=1, | |
value=1) | |
seed = gr.Slider(label='Seed', | |
minimum=0, | |
maximum=100000, | |
step=1, | |
value=0) | |
with gr.Accordion('Other Parameters', open=False): | |
num_steps = gr.Slider(label='Number of Steps', | |
minimum=0, | |
maximum=100, | |
step=1, | |
value=50) | |
guidance_scale = gr.Slider(label='CFG Scale', | |
minimum=0, | |
maximum=50, | |
step=0.1, | |
value=7.5) | |
run_button = gr.Button('Generate') | |
gr.Markdown(''' | |
- It takes a few minutes to download model first. | |
- Expected time to generate an 8-frame video: 70 seconds with T4, 24 seconds with A10G, (10 seconds with A100) | |
''') | |
with gr.Column(): | |
result = gr.Video(label='Result') | |
with gr.Row(): | |
examples = [ | |
[ | |
'Tune-A-Video-library/a-man-is-surfing', | |
'A panda is surfing.', | |
8, | |
1, | |
3, | |
50, | |
7.5, | |
], | |
[ | |
'Tune-A-Video-library/a-man-is-surfing', | |
'A racoon is surfing, cartoon style.', | |
8, | |
1, | |
3, | |
50, | |
7.5, | |
], | |
[ | |
'Tune-A-Video-library/mo-di-bear-guitar', | |
'a handsome prince is playing guitar, modern disney style.', | |
8, | |
1, | |
123, | |
50, | |
7.5, | |
], | |
[ | |
'Tune-A-Video-library/mo-di-bear-guitar', | |
'a magical princess is playing guitar, modern disney style.', | |
8, | |
1, | |
123, | |
50, | |
7.5, | |
], | |
[ | |
'Tune-A-Video-library/mo-di-bear-guitar', | |
'a rabbit is playing guitar, modern disney style.', | |
8, | |
1, | |
123, | |
50, | |
7.5, | |
], | |
[ | |
'Tune-A-Video-library/mo-di-bear-guitar', | |
'a baby is playing guitar, modern disney style.', | |
8, | |
1, | |
123, | |
50, | |
7.5, | |
], | |
[ | |
'Tune-A-Video-library/redshift-man-skiing', | |
'(redshift style) spider man is skiing.', | |
8, | |
1, | |
123, | |
50, | |
7.5, | |
], | |
[ | |
'Tune-A-Video-library/redshift-man-skiing', | |
'(redshift style) black widow is skiing.', | |
8, | |
1, | |
123, | |
50, | |
7.5, | |
], | |
[ | |
'Tune-A-Video-library/redshift-man-skiing', | |
'(redshift style) batman is skiing.', | |
8, | |
1, | |
123, | |
50, | |
7.5, | |
], | |
[ | |
'Tune-A-Video-library/redshift-man-skiing', | |
'(redshift style) hulk is skiing.', | |
8, | |
1, | |
123, | |
50, | |
7.5, | |
], | |
] | |
gr.Examples(examples=examples, | |
inputs=[ | |
model_id, | |
prompt, | |
video_length, | |
fps, | |
seed, | |
num_steps, | |
guidance_scale, | |
], | |
outputs=result, | |
fn=pipe.run, | |
cache_examples=os.getenv('SYSTEM') == 'spaces') | |
model_id.change(fn=app.load_model_info, | |
inputs=model_id, | |
outputs=[ | |
base_model_used_for_training, | |
prompt_used_for_training, | |
]) | |
inputs = [ | |
model_id, | |
prompt, | |
video_length, | |
fps, | |
seed, | |
num_steps, | |
guidance_scale, | |
] | |
prompt.submit(fn=pipe.run, inputs=inputs, outputs=result) | |
run_button.click(fn=pipe.run, inputs=inputs, outputs=result) | |
demo.queue().launch() | |