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Browse files- .pre-commit-config.yaml +36 -0
- .style.yapf +5 -0
- .vscode/settings.json +18 -0
- LICENSE +21 -0
- README.md +2 -1
- app.py +132 -0
- requirements.txt +9 -0
- style.css +9 -0
.pre-commit-config.yaml
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repos:
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- repo: https://github.com/pre-commit/pre-commit-hooks
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rev: v4.2.0
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hooks:
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- id: check-executables-have-shebangs
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- id: check-json
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- id: check-merge-conflict
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- id: check-shebang-scripts-are-executable
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- id: check-toml
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- id: check-yaml
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- id: double-quote-string-fixer
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- id: end-of-file-fixer
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- id: mixed-line-ending
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args: ['--fix=lf']
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- id: requirements-txt-fixer
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- id: trailing-whitespace
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- repo: https://github.com/myint/docformatter
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rev: v1.4
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hooks:
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- id: docformatter
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args: ['--in-place']
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- repo: https://github.com/pycqa/isort
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rev: 5.12.0
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hooks:
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- id: isort
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- repo: https://github.com/pre-commit/mirrors-mypy
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rev: v0.991
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hooks:
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- id: mypy
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args: ['--ignore-missing-imports']
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additional_dependencies: ['types-python-slugify']
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- repo: https://github.com/google/yapf
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rev: v0.32.0
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hooks:
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- id: yapf
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args: ['--parallel', '--in-place']
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.style.yapf
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[style]
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based_on_style = pep8
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blank_line_before_nested_class_or_def = false
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spaces_before_comment = 2
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split_before_logical_operator = true
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.vscode/settings.json
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{
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"python.linting.enabled": true,
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"python.linting.flake8Enabled": true,
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"python.linting.pylintEnabled": false,
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"python.linting.lintOnSave": true,
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"python.formatting.provider": "yapf",
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"python.formatting.yapfArgs": [
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"--style={based_on_style: pep8, indent_width: 4, blank_line_before_nested_class_or_def: false, spaces_before_comment: 2, split_before_logical_operator: true}"
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],
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"[python]": {
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"editor.formatOnType": true,
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"editor.codeActionsOnSave": {
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"source.organizeImports": true
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}
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},
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"editor.formatOnSave": true,
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"files.insertFinalNewline": true
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}
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LICENSE
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MIT License
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Copyright (c) 2023 hysts
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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README.md
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---
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-
title: Zeroscope V2
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emoji: 🌖
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colorFrom: gray
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colorTo: purple
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app_file: app.py
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pinned: false
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license: mit
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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---
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title: Zeroscope V2
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emoji: 🌖
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colorFrom: gray
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colorTo: purple
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app_file: app.py
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pinned: false
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license: mit
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suggested_hardware: t4-small
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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app.py
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#!/usr/bin/env python
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from __future__ import annotations
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import os
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import random
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import tempfile
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import gradio as gr
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import imageio
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import numpy as np
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import torch
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from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
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DESCRIPTION = '# zeroscope v2'
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if not torch.cuda.is_available():
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DESCRIPTION += '\n<p>Running on CPU 🥶 This demo does not work on CPU.</p>'
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if (SPACE_ID := os.getenv('SPACE_ID')) is not None:
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DESCRIPTION += f'\n<p>For faster inference without waiting in queue, you may duplicate the space and upgrade to GPU in settings. <a href="https://huggingface.co/spaces/{SPACE_ID}?duplicate=true"><img style="display: inline; margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space" /></a></p>'
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MAX_NUM_FRAMES = int(os.getenv('MAX_NUM_FRAMES', '200'))
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DEFAULT_NUM_FRAMES = min(MAX_NUM_FRAMES,
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int(os.getenv('DEFAULT_NUM_FRAMES', '24')))
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MAX_SEED = np.iinfo(np.int32).max
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pipe = DiffusionPipeline.from_pretrained('cerspense/zeroscope_v2_576w',
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torch_dtype=torch.float16)
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pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
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pipe.enable_model_cpu_offload()
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pipe.enable_vae_slicing()
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def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
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if randomize_seed:
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seed = random.randint(0, MAX_SEED)
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return seed
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def to_video(frames: list[np.ndarray], fps: int) -> str:
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out_file = tempfile.NamedTemporaryFile(suffix='.mp4', delete=False)
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writer = imageio.get_writer(out_file.name, format='FFMPEG', fps=fps)
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for frame in frames:
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writer.append_data(frame)
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writer.close()
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return out_file.name
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def generate(prompt: str, seed: int, num_frames: int,
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num_inference_steps: int) -> str:
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generator = torch.Generator().manual_seed(seed)
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frames = pipe(prompt,
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num_inference_steps=num_inference_steps,
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num_frames=num_frames,
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width=576,
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height=320,
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generator=generator).frames
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return to_video(frames, 8)
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examples = [
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['An astronaut riding a horse', 0, 24, 25],
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['A panda eating bamboo on a rock', 0, 24, 25],
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['Spiderman is surfing', 0, 24, 25],
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]
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with gr.Blocks(css='style.css') as demo:
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gr.Markdown(DESCRIPTION)
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with gr.Box():
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with gr.Row():
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prompt = gr.Text(label='Prompt',
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show_label=False,
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max_lines=1,
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placeholder='Enter your prompt',
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container=False)
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run_button = gr.Button('Generate video', scale=0)
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result = gr.Video(label='Result', show_label=False)
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with gr.Accordion('Advanced options', open=False):
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seed = gr.Slider(label='Seed',
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minimum=0,
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maximum=MAX_SEED,
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step=1,
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value=0)
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randomize_seed = gr.Checkbox(label='Randomize seed', value=True)
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num_frames = gr.Slider(
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label='Number of frames',
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minimum=24,
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maximum=MAX_NUM_FRAMES,
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step=1,
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value=24,
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info=
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'Note that the content of the video also changes when you change the number of frames.'
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)
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num_inference_steps = gr.Slider(label='Number of inference steps',
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minimum=10,
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maximum=50,
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step=1,
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value=25)
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inputs = [
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prompt,
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seed,
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num_frames,
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num_inference_steps,
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]
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gr.Examples(examples=examples,
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inputs=inputs,
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outputs=result,
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fn=generate,
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cache_examples=os.getenv('CACHE_EXAMPLES') == '1')
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prompt.submit(
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fn=randomize_seed_fn,
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inputs=[seed, randomize_seed],
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outputs=seed,
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queue=False,
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).then(
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fn=generate,
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inputs=inputs,
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outputs=result,
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api_name='run',
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)
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run_button.click(
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fn=randomize_seed_fn,
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inputs=[seed, randomize_seed],
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outputs=seed,
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queue=False,
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).then(
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fn=generate,
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inputs=inputs,
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outputs=result,
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)
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demo.queue(max_size=10).launch()
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requirements.txt
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accelerate==0.20.3
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diffusers==0.17.1
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gradio==3.35.2
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huggingface-hub==0.15.1
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imageio[ffmpeg]==2.31.1
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torch==2.0.1
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torchvision==0.15.2
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transformers==4.30.2
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xformers==0.0.20
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style.css
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h1 {
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text-align: center;
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}
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#component-0 {
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max-width: 730px;
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margin: auto;
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padding-top: 1.5rem;
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}
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