49 lines
1.6 KiB
Markdown
49 lines
1.6 KiB
Markdown
# 部署步骤
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1. 将该仓库clone到本地
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2. 创建虚拟环境并启动
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``` shell
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conda create -n takway python=3.9
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conda activate takway
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```
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3. cd进入仓库目录下，安装依赖
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``` shell
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cd ~/TakwayDisplayPlatform
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pip install -r requirements.txt
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```
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4. 在./utils/目录下创建vits_model文件夹
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从[链接](https://huggingface.co/spaces/zomehwh/vits-uma-genshin-honkai/tree/main/model)下载vits_model并放入该文件夹下，只需下载config.json和G_953000.pth即可
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5. 在./utils/bert_vits2/目录下创建bert，slm文件夹
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从[链接1](https://huggingface.co/hfl/chinese-roberta-wwm-ext-large)，[链接2](https://huggingface.co/microsoft/deberta-v3-large)，[链接3](https://huggingface.co/ku-nlp/deberta-v2-large-japanese-char-wwm)下载模型，放入bert目录下
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从[链接4](https://huggingface.co/microsoft/wavlm-base-plus)下载模型，放入slm目录下
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在./utils/bert_vits2/bert目录下创建bert_models.json文件，填入如下内容
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``` json
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{
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"deberta-v2-large-japanese-char-wwm": {
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"repo_id": "ku-nlp/deberta-v2-large-japanese-char-wwm",
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"files": ["pytorch_model.bin"]
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},
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"chinese-roberta-wwm-ext-large": {
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"repo_id": "hfl/chinese-roberta-wwm-ext-large",
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"files": ["pytorch_model.bin"]
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},
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"deberta-v3-large": {
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"repo_id": "microsoft/deberta-v3-large",
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"files": ["spm.model", "pytorch_model.bin"]
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}
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}
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```
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6. 在 ./utils/bert_vits2/data/mix/目录下创建models文件夹，并放入预训练模型250000_G.pth
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7. 回到根目录，`python main.py`启动程序
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