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https://github.com/SWivid/F5-TTS.git
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@@ -30,6 +30,9 @@
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# Create a conda env with python_version>=3.10 (you could also use virtualenv)
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conda create -n f5-tts python=3.11
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conda activate f5-tts
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# Install FFmpeg if you haven't yet
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conda install ffmpeg
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```
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### Install PyTorch with matched device
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@@ -39,7 +42,11 @@ conda activate f5-tts
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> ```bash
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> # Install pytorch with your CUDA version, e.g.
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> pip install torch==2.8.0+cu128 torchaudio==2.8.0+cu128 --extra-index-url https://download.pytorch.org/whl/cu128
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>
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> # And also possible previous versions, e.g.
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> pip install torch==2.4.0+cu124 torchaudio==2.4.0+cu124 --extra-index-url https://download.pytorch.org/whl/cu124
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> # etc.
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> ```
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</details>
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@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
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[project]
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name = "f5-tts"
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version = "1.1.10"
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version = "1.1.11"
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description = "F5-TTS: A Fairytaler that Fakes Fluent and Faithful Speech with Flow Matching"
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readme = "README.md"
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license = {text = "MIT License"}
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@@ -20,7 +20,7 @@ dependencies = [
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"click",
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"datasets",
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"ema_pytorch>=0.5.2",
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"gradio>=5.0.0",
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"gradio>=6.0.0",
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"hydra-core>=1.3.0",
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"librosa",
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"matplotlib",
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@@ -577,7 +577,7 @@ with gr.Blocks() as app_multistyle:
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label="Cherry-pick Interface",
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lines=10,
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max_lines=40,
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show_copy_button=True,
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buttons=["copy"], # show_copy_button=True if gradio<6.0
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interactive=False,
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visible=False,
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)
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