mirror of
https://github.com/RVC-Boss/GPT-SoVITS.git
synced 2025-04-29 22:10:21 +08:00
Colab Infer Fix (#2322)
* Update Colab Infer, Add NLTK Download * Rename GPT_SoVITS_Inference.ipynb to Colab-Inference.ipynb * Rename * Update URL * .
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Colab-Inference.ipynb
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184
Colab-Inference.ipynb
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# GPT-SoVITS Infer"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Env Setup (Run Once Only)\n",
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"## 环境配置, 只需运行一次"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### 1."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "e9b7iFV3dm1f"
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},
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"outputs": [],
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"source": [
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"%%writefile /content/setup.sh\n",
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"set -e\n",
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"\n",
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"cd /content\n",
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"\n",
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"git clone https://github.com/RVC-Boss/GPT-SoVITS.git\n",
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"\n",
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"cd GPT-SoVITS\n",
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"\n",
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"mkdir GPT_weights\n",
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"\n",
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"mkdir SoVITS_weights\n",
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"\n",
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"if conda env list | awk '{print $1}' | grep -Fxq \"GPTSoVITS\"; then\n",
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" :\n",
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"else\n",
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" conda create -n GPTSoVITS python=3.10 -y\n",
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"fi\n",
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"\n",
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"source activate GPTSoVITS\n",
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"\n",
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"pip install ipykernel\n",
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"\n",
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"bash install.sh --source HF"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### 2."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"cellView": "form",
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"id": "0NgxXg5sjv7z"
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},
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"outputs": [],
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"source": [
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"%pip install -q condacolab\n",
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"import condacolab\n",
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"condacolab.install_from_url(\"https://repo.anaconda.com/archive/Anaconda3-2024.10-1-Linux-x86_64.sh\")\n",
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"!cd /content && bash setup.sh"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Download Model"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Download From HuggingFace"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"cellView": "form",
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"id": "vbZY-LnM0tzq"
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},
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"outputs": [],
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"source": [
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"# Modify These\n",
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"USER_ID = \"AkitoP\"\n",
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"REPO_NAME = \"GPT-SoVITS-v2-aegi\"\n",
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"BRANCH = \"main\"\n",
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"GPT_PATH = \"new_aegigoe-e100.ckpt\"\n",
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"SOVITS_PATH = \"new_aegigoe_e60_s32220.pth\"\n",
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"\n",
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"# Do Not Modify\n",
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"HF_BASE = \"https://huggingface.co\"\n",
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"REPO_ID = f\"{USER_ID}/{REPO_NAME}\"\n",
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"GPT_URL = f\"{HF_BASE}/{REPO_ID}/blob/{BRANCH}/{GPT_PATH}\"\n",
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"SOVITS_URL = f\"{HF_BASE}/{REPO_ID}/blob/{BRANCH}/{SOVITS_PATH}\"\n",
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"\n",
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"!cd \"/content/GPT-SoVITS/GPT_weights\" && wget \"{GPT_URL}\"\n",
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"!cd \"/content/GPT-SoVITS/SoVITS_weights\" && wget \"{SOVITS_URL}\"\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Download From ModelScope"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Modify These\n",
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"USER_ID = \"aihobbyist\"\n",
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"REPO_NAME = \"GPT-SoVits-V2-models\"\n",
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"BRANCH = \"master\"\n",
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"GPT_PATH = \"Genshin_Impact/EN/GPT_GenshinImpact_EN_5.1.ckpt\"\n",
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"SOVITS_PATH = \"Wuthering_Waves/CN/SV_WutheringWaves_CN_1.3.pth\"\n",
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"\n",
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"# Do Not Modify\n",
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"HF_BASE = \"https://www.modelscope.cn/models\"\n",
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"REPO_ID = f\"{USER_ID}/{REPO_NAME}\"\n",
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"GPT_URL = f\"{HF_BASE}/{REPO_ID}/resolve/{BRANCH}/{GPT_PATH}\"\n",
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"SOVITS_URL = f\"{HF_BASE}/{REPO_ID}/resolve/{BRANCH}/{SOVITS_PATH}\"\n",
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"\n",
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"!cd \"/content/GPT-SoVITS/GPT_weights\" && wget \"{GPT_URL}\"\n",
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"!cd \"/content/GPT-SoVITS/SoVITS_weights\" && wget \"{SOVITS_URL}\""
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Launch WebUI\n",
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"# 启动 WebUI"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"cellView": "form",
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"id": "4oRGUzkrk8C7"
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},
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"outputs": [],
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"source": [
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"!cd /content/GPT-SoVITS && source activate GPTSoVITS && export is_share=True && python webui.py"
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]
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}
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],
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"metadata": {
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"accelerator": "GPU",
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"colab": {
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"provenance": []
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},
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"kernelspec": {
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"display_name": "Python 3",
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"name": "python3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}
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@ -10,21 +10,28 @@
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"<a href=\"https://colab.research.google.com/github/RVC-Boss/GPT-SoVITS/blob/main/colab_webui.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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"<a href=\"https://colab.research.google.com/github/RVC-Boss/GPT-SoVITS/blob/main/colab_webui.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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]
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]
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},
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# GPT-SoVITS WebUI"
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]
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},
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{
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{
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"cell_type": "markdown",
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"cell_type": "markdown",
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"metadata": {
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"metadata": {
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"id": "_o6a8GS2lWQM"
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"id": "_o6a8GS2lWQM"
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},
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},
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"source": [
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"source": [
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"# Env Setup (Run Once Only)\n",
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"## Env Setup (Run Once Only)\n",
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"# 环境配置, 只需运行一次"
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"## 环境配置, 只需运行一次"
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]
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]
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},
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},
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{
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{
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"cell_type": "markdown",
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"cell_type": "markdown",
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"metadata": {},
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"metadata": {},
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"source": [
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"source": [
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"## 1."
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"### 1."
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]
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]
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},
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},
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{
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{
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"source": [
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"source": [
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"%%writefile /content/setup.sh\n",
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"%%writefile /content/setup.sh\n",
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"set -e\n",
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"set -e\n",
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"\n",
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"cd /content\n",
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"cd /content\n",
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"rm -rf GPT-SoVITS\n",
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"\n",
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"git clone https://github.com/RVC-Boss/GPT-SoVITS.git\n",
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"git clone https://github.com/RVC-Boss/GPT-SoVITS.git\n",
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"\n",
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"cd GPT-SoVITS\n",
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"cd GPT-SoVITS\n",
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"\n",
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"\n",
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"if conda env list | awk '{print $1}' | grep -Fxq \"GPTSoVITS\"; then\n",
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"if conda env list | awk '{print $1}' | grep -Fxq \"GPTSoVITS\"; then\n",
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"\n",
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"\n",
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"source activate GPTSoVITS\n",
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"source activate GPTSoVITS\n",
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"\n",
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"\n",
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"pip install ipykernel\n",
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"\n",
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"bash install.sh --source HF --download-uvr5"
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"bash install.sh --source HF --download-uvr5"
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]
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]
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},
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},
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"cell_type": "markdown",
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"cell_type": "markdown",
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"metadata": {},
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"metadata": {},
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"source": [
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"source": [
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"## 2."
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"### 2."
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]
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]
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},
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},
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{
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{
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"cell_type": "markdown",
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"cell_type": "markdown",
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"metadata": {},
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"metadata": {},
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"source": [
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"source": [
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"# Launch WebUI\n",
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"## Launch WebUI\n",
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"# 启动 WebUI"
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"## 启动 WebUI"
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]
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]
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},
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},
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{
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{
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "himHYZmra7ix"
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},
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"source": [
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"# Credits for bubarino giving me the huggingface import code (感谢 bubarino 给了我 huggingface 导入代码)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "e9b7iFV3dm1f"
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},
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"outputs": [],
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"source": [
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"!git clone https://github.com/RVC-Boss/GPT-SoVITS.git\n",
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"%cd GPT-SoVITS\n",
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"!apt-get update && apt-get install -y --no-install-recommends tzdata ffmpeg libsox-dev parallel aria2 git git-lfs && git lfs install\n",
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"!pip install -r extra-req.txt --no-deps\n",
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"!pip install -r requirements.txt"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"cellView": "form",
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"id": "0NgxXg5sjv7z"
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},
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"outputs": [],
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"source": [
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"# @title Download pretrained models 下载预训练模型\n",
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"!mkdir -p /content/GPT-SoVITS/GPT_SoVITS/pretrained_models\n",
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"!mkdir -p /content/GPT-SoVITS/tools/damo_asr/models\n",
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"!mkdir -p /content/GPT-SoVITS/tools/uvr5\n",
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"%cd /content/GPT-SoVITS/GPT_SoVITS/pretrained_models\n",
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"!git clone https://huggingface.co/lj1995/GPT-SoVITS\n",
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"%cd /content/GPT-SoVITS/tools/damo_asr/models\n",
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"!git clone https://www.modelscope.cn/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch.git\n",
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"!git clone https://www.modelscope.cn/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch.git\n",
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"!git clone https://www.modelscope.cn/damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch.git\n",
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"# @title UVR5 pretrains 安装uvr5模型\n",
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"%cd /content/GPT-SoVITS/tools/uvr5\n",
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"!git clone https://huggingface.co/Delik/uvr5_weights\n",
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"!git config core.sparseCheckout true\n",
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"!mv /content/GPT-SoVITS/GPT_SoVITS/pretrained_models/GPT-SoVITS/* /content/GPT-SoVITS/GPT_SoVITS/pretrained_models/"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"cellView": "form",
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"id": "cPDEH-9czOJF"
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},
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"outputs": [],
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"source": [
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"#@title Create folder models 创建文件夹模型\n",
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"import os\n",
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"base_directory = \"/content/GPT-SoVITS\"\n",
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"folder_names = [\"SoVITS_weights\", \"GPT_weights\"]\n",
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"\n",
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"for folder_name in folder_names:\n",
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" if os.path.exists(os.path.join(base_directory, folder_name)):\n",
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" print(f\"The folder '{folder_name}' already exists. (文件夹'{folder_name}'已经存在。)\")\n",
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" else:\n",
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" os.makedirs(os.path.join(base_directory, folder_name))\n",
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" print(f\"The folder '{folder_name}' was created successfully! (文件夹'{folder_name}'已成功创建！)\")\n",
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"\n",
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"print(\"All folders have been created. (所有文件夹均已创建。)\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"cellView": "form",
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"id": "vbZY-LnM0tzq"
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},
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"outputs": [],
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"source": [
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"import requests\n",
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"import zipfile\n",
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"import shutil\n",
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"import os\n",
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"\n",
|
|
||||||
"#@title Import model 导入模型 (HuggingFace)\n",
|
|
||||||
"hf_link = 'https://huggingface.co/modelloosrvcc/Nagisa_Shingetsu_GPT-SoVITS/resolve/main/Nagisa.zip' #@param {type: \"string\"}\n",
|
|
||||||
"\n",
|
|
||||||
"output_path = '/content/'\n",
|
|
||||||
"\n",
|
|
||||||
"response = requests.get(hf_link)\n",
|
|
||||||
"with open(output_path + 'file.zip', 'wb') as file:\n",
|
|
||||||
" file.write(response.content)\n",
|
|
||||||
"\n",
|
|
||||||
"with zipfile.ZipFile(output_path + 'file.zip', 'r') as zip_ref:\n",
|
|
||||||
" zip_ref.extractall(output_path)\n",
|
|
||||||
"\n",
|
|
||||||
"os.remove(output_path + \"file.zip\")\n",
|
|
||||||
"\n",
|
|
||||||
"source_directory = output_path\n",
|
|
||||||
"SoVITS_destination_directory = '/content/GPT-SoVITS/SoVITS_weights'\n",
|
|
||||||
"GPT_destination_directory = '/content/GPT-SoVITS/GPT_weights'\n",
|
|
||||||
"\n",
|
|
||||||
"for filename in os.listdir(source_directory):\n",
|
|
||||||
" if filename.endswith(\".pth\"):\n",
|
|
||||||
" source_path = os.path.join(source_directory, filename)\n",
|
|
||||||
" destination_path = os.path.join(SoVITS_destination_directory, filename)\n",
|
|
||||||
" shutil.move(source_path, destination_path)\n",
|
|
||||||
"\n",
|
|
||||||
"for filename in os.listdir(source_directory):\n",
|
|
||||||
" if filename.endswith(\".ckpt\"):\n",
|
|
||||||
" source_path = os.path.join(source_directory, filename)\n",
|
|
||||||
" destination_path = os.path.join(GPT_destination_directory, filename)\n",
|
|
||||||
" shutil.move(source_path, destination_path)\n",
|
|
||||||
"\n",
|
|
||||||
"print(f'Model downloaded. (模型已下载。)')"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": null,
|
|
||||||
"metadata": {
|
|
||||||
"cellView": "form",
|
|
||||||
"id": "4oRGUzkrk8C7"
|
|
||||||
},
|
|
||||||
"outputs": [],
|
|
||||||
"source": [
|
|
||||||
"# @title launch WebUI 启动WebUI\n",
|
|
||||||
"!/usr/local/bin/pip install ipykernel\n",
|
|
||||||
"!sed -i '10s/False/True/' /content/GPT-SoVITS/config.py\n",
|
|
||||||
"%cd /content/GPT-SoVITS/\n",
|
|
||||||
"!/usr/local/bin/python webui.py"
|
|
||||||
]
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"metadata": {
|
|
||||||
"accelerator": "GPU",
|
|
||||||
"colab": {
|
|
||||||
"provenance": []
|
|
||||||
},
|
|
||||||
"kernelspec": {
|
|
||||||
"display_name": "Python 3",
|
|
||||||
"name": "python3"
|
|
||||||
}
|
|
||||||
},
|
|
||||||
"nbformat": 4,
|
|
||||||
"nbformat_minor": 0
|
|
||||||
}
|
|
||||||
2
api.py
2
api.py
@ -534,7 +534,7 @@ class DictToAttrRecursive(dict):
|
|||||||
|
|
||||||
|
|
||||||
def get_spepc(hps, filename):
|
def get_spepc(hps, filename):
|
||||||
audio, _ = librosa.load(filename, int(hps.data.sampling_rate))
|
audio, _ = librosa.load(filename, sr=int(hps.data.sampling_rate))
|
||||||
audio = torch.FloatTensor(audio)
|
audio = torch.FloatTensor(audio)
|
||||||
maxx = audio.abs().max()
|
maxx = audio.abs().max()
|
||||||
if maxx > 1:
|
if maxx > 1:
|
||||||
|
|||||||
@ -1,5 +1,13 @@
|
|||||||
{
|
{
|
||||||
"cells": [
|
"cells": [
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"id": "9fd922fb",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"# Deprecated"
|
||||||
|
]
|
||||||
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": null,
|
"execution_count": null,
|
||||||
|
|||||||
@ -202,6 +202,8 @@ pip install -r extra-req.txt --no-deps
|
|||||||
|
|
||||||
pip install -r requirements.txt
|
pip install -r requirements.txt
|
||||||
|
|
||||||
|
python -c "import nltk; nltk.download(['averaged_perceptron_tagger','averaged_perceptron_tagger_eng','cmudict'])"
|
||||||
|
|
||||||
if [ "$USE_ROCM" = true ] && [ "$IS_WSL" = true ]; then
|
if [ "$USE_ROCM" = true ] && [ "$IS_WSL" = true ]; then
|
||||||
echo "Update to WSL compatible runtime lib..."
|
echo "Update to WSL compatible runtime lib..."
|
||||||
location=$(pip show torch | grep Location | awk -F ": " '{print $2}')
|
location=$(pip show torch | grep Location | awk -F ": " '{print $2}')
|
||||||
|
|||||||
Loading…
x
Reference in New Issue
Block a user