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F5 tts (#59)
* init tts/F5-TTS * epic hax to download ckpts * clear default reference audio/text from inference vars * allow blank inputs for inference-cli to just pull checkpoints without running inference * f5-tts github workflow to publish docker images
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# Base CUDA image
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FROM cnstark/pytorch:2.3.1-py3.10.15-cuda12.1.0-devel-ubuntu22.04
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# Set environment variables
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ENV DEBIAN_FRONTEND=noninteractive
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ENV TZ=Etc/UTC
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# Install necessary packages and git-lfs
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RUN apt-get update && \
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apt-get install -y --no-install-recommends \
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tzdata \
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ffmpeg \
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parallel \
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git \
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nano \
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curl \
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software-properties-common \
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sudo \
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rsync && \
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curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | bash && \
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apt-get install -y git-lfs && \
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git lfs install && \
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add-apt-repository ppa:deadsnakes/ppa && \
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rm -rf /var/lib/apt/lists/*
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# Create directories for Python installation and model code
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RUN mkdir -p /python_install /model_code/F5-TTS
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# Set the working directory for Python installation
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WORKDIR /python_install
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# Copy the requirements.txt and install Python dependencies
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COPY requirements*.txt /python_install/
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# copies create real copies of python executable instead of symlinks, to make the virtualenv relocatable
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RUN python3 -m venv --copies python && \
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python/bin/pip install --upgrade pip wheel setuptools && \
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python/bin/pip install --no-cache-dir -r requirements.txt -r requirements_eval.txt
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WORKDIR /model_code/F5-TTS
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# Copy the remaining contents to the model_code directory
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COPY . /model_code/F5-TTS
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# /model_code/F5-TTS/pretrained_models
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ARG HF_DATASETS_CACHE="./pretrained_models"
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# FIXME: this might not work without HF_TOKEN!!!
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ENV HF_DATASETS_CACHE=$HF_DATASETS_CACHE
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# initializes the model - downloads checkpoints
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RUN ["/bin/bash", "-c", "HF_DATASETS_CACHE=$HF_DATASETS_CACHE DOWNLOAD_ONLY=TRUE /python_install/python/bin/python inference-cli.py"]
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ENTRYPOINT ["/bin/bash", "-c", ". /python_install/python/bin/activate && exec /bin/bash"]
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