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--- |
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pipeline_tag: text-to-video |
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license: cc-by-nc-4.0 |
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--- |
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# Info |
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- base model [zeroscope_v2_576w](https://huggingface.co/cerspense/zeroscope_v2_576w). |
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- Train on [potat1](https://huggingface.co/camenduru/potat1#dataset--config) [dataset](https://huggingface.co/camenduru/potat1_dataset) with 50000 steps for 10 hours on single GPU of 24GB VRAM. |
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# Install Windows |
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```batch |
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git clone https://github.com/ExponentialML/Text-To-Video-Finetuning.git |
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cd Text-To-Video-Finetuning |
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git lfs install |
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git clone https://huggingface.co/damo-vilab/text-to-video-ms-1.7b ./models/model_scope_diffusers/ |
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py -m venv --clear venv && venv\Scripts\activate |
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pip install -r requirements.txt |
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pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118 --no-cache --force-reinstall --version --isolated --ignore-installed |
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git clone https://github.com/ExponentialML/Video-BLIP2-Preprocessor.git |
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cd Video-BLIP2-Preprocessor |
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pip install -r requirements.txt |
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:: fix1 |
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echo accelerate^>=0.20.3>>requirements-dev.txt |
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pip install -r requirements-dev.txt |
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:: Captation |
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python preprocess.py --video_directory C:\Video-BLIP2-Preprocessor\videos --config_name "My Videos" --config_save_name "my_videos" |
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:: Training |
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venv\Scripts\activate && python train.py --config ./configs/v2/train_config.yaml |
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:: inference 1024x576 |
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python inference.py --model zeroscope_v2_576w_potat1\zeroscope_v2_576w-checkpoint-50000 --prompt "a fast moving fancy sports car" --fps 24 --num-frames 30 --window-size 12 --width 1024 --height 576 --sdp |
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``` |
