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# Audiocraft | ||
Audiocraft是一个基于深度学习的音频处理和生成库。它具有最先进的编码器音频压缩器/标记器,以及MusicGen,一个简单而可控的音乐生成LM,具有文本和旋律调节。 | ||
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Audiocraft is a library for audio processing and generation with deep learning. It features the state-of-the-art EnCodec audio compressor / tokenizer, along with MusicGen, a simple and controllable music generation LM with textual and melodic conditioning. | ||
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# usage | ||
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``` | ||
docker run -it -d -p 7862:7860 --gpus all initialencounter/audiocraft:latest bash -c "bash .start.sh" | ||
``` |
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# ChatRWKV |
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{ | ||
"label": "Docker 镜像", | ||
"position": 5 | ||
} |
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# openai-whisper-api | ||
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将请求的格式改为base64 | ||
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适用于koishi-plugin-whisper-asr [![npm](https://img.shields.io/npm/v/koishi-plugin-whisper-asr?style=flat-square)](https://www.npmjs.com/package/koishi-plugin-whisper-asr) | ||
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搭配[adapter-wechaty](https://www.npmjs.com/package/@initencounter/koishi-plugin-adapter-wechaty)及[![npm](https://img.shields.io/npm/v/koishi-plugin-davinci-003?style=flat-square)](https://www.npmjs.com/package/koishi-plugin-davinci-003)可以在微信搭建语音回复的ChatGPT机器人 | ||
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部署方法 | ||
``` | ||
docker run -d --gpus all -p 9000:9000 -e ASR_MODEL=base -e ASR_ENGINE=openai_whisper initialencounter/openai-whisper-asr-webservice:latest-gpu | ||
``` |
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# PaddleSpeech | ||
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``` | ||
docker run -it -p 8880-8889:8880-8889 --gpus all initialencounter/paddlespeech:ttsfinetune-latest /bin/bash | ||
``` | ||
镜像集成了 jupyterlab,进入容器后,可通过以下命令开启服务。 | ||
``` | ||
jupyter lab --ip=0.0.0.0 --port=8880 --allow-root --notebook-dir=/home/aistudio | ||
``` | ||
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## Finetune 教程 | ||
参考自[【有手就行】使用自己的声音做语音合成](https://aistudio.baidu.com/aistudio/projectdetail/5003396) | ||
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- 1.将你的语音文件放到 work/init 目录下 | ||
>可通过 docker cp 或者 scp 将你的语音文件放到这个目录 | ||
>语音文件要求 | ||
- 2.开始训练 | ||
- 对于萌新 | ||
>直接运行```python main.py``` | ||
- 有一定深度学习经验的朋友 | ||
>可以编辑 main.py 里的代码 | ||
>根据自己的需要来微调模型 | ||
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## 同时支持将微调后的模型部署为 FastAPI | ||
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- 修改app.py文件 | ||
```shell | ||
cd /home/aistudio/initialencunter/PaddleSpeech | ||
``` | ||
```python | ||
# 将 model 替换为你的exp_name | ||
am_inference_dir = os.path.abspath("/home/aistudio/inferrence/init") | ||
# 如果你的 exp_name 为 "demo" | ||
# 则将代码修改为 | ||
am_inference_dir = os.path.abspath("/home/aistudio/inferrence/demo") | ||
``` | ||
- 启动接口 | ||
```shell | ||
python app.py | ||
``` | ||
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## 问题反馈 | ||
* QQ群:399899914 | ||
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* 小伙伴如果遇到问题或者有新的想法,欢迎到[这里](https://github.com/initialencounter/mykoishi/issues)反馈哦~ | ||
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语音文件要求 | ||
> 对于语音合成任务,对数据是有一定要求的,尽可能上传干净的人声数据,比如像示例中的人声数据,在安静环境下录制,录制设备无论是手机,电脑,还是别的设备都可以,注意一定要控制噪音,或者提前使用音频剪辑软件进行降噪。(一定要是中文数据,这个项目目前只支持中文数据!!其它语言预标注环节会出错!) | ||
- 1.音频不要太长,也不要太短,2s~10s之间,音频太长会报错! | ||
- 2.音频尽量是干净人声,不要有BGM,不要有比较大的杂音,不要有一些奇奇怪怪的声效,比如回声等 | ||
- 3.声音的情绪尽量稳定,以说话的语料为主,不要是『嗯』『啊』『哈』之类的语气词 | ||
- 4.音频数量大于5 条!!否则会报错!! | ||
关于录音工具的选择: | ||
你可以使用一些在线运行的录音工具或者 【Adobe Audition】,【Cool Edit Pro】, 【Audacity】 等录音软件录制音频,保存为 24000采样率的 Wav 格式 | ||
也可以通过手机录音后,使用格式工厂等格式转换软件,将手机录音转换成 Wav 格式后上传到这个项目中。 |
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# stable diffusion webui | ||
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# usage | ||
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``` | ||
docker run -it -d -p 7860:7860 --gpus all initialencounter/sd-webui:latest bash -c "bash start.sh" | ||
``` | ||
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如过你在宿主机上下载了模型可以使用以下命令,挂载目录到容器: | ||
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``` | ||
docker run -v 模型目录/models:/stable-diffusion-webui/models -it -d -p 7860:7860 --gpus all initialencounter/sd-webui:latest bash -c "bash start.sh" | ||
``` |
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# text-gen-webui | ||
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## usage | ||
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``` | ||
docker run --gpus all -d -it -p 7860:7860 initialencounter/text-gen-webui:latest | ||
``` | ||
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## start | ||
``` | ||
conda activate textgen; | ||
cd /text-generation-webui; | ||
python server.py --api --listen --listen-host "0.0.0.0" --listen-port 7860 | ||
``` |
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# wechaty | ||
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## 准备 | ||
* openai apikey | ||
* 开通过微信支付的微信账号,(不开通微信支付可能会登不上) | ||
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## 步骤 | ||
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- 1.启动容器 | ||
- `docker run -p 5141:5140 initialencounter/koishi-wechaty:latest bash -c "cd /koimux_bot && yarn start"` | ||
- 2.扫码 | ||
- `docker logs 容器ID`或者直接登录koishi控制台 | ||
- 3.配置davinci-003 | ||
- 输入key,启用插件 | ||
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## 联系我 | ||
- qq群:399899914 | ||
- 哔哩哔哩:https://space.bilibili.com/225995995 |
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# koishi-plugin-arcadia | ||
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[![npm](https://img.shields.io/npm/v/koishi-plugin-arcadia?style=flat-square)](https://www.npmjs.com/package/koishi-plugin-arcadia) | ||
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意间Ai绘画(yjart),支持100多个模型 | ||
因为懒只写了9个,后面会加上 | ||
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![alt 示例2](https://raw.githubusercontent.com/initialencounter/mykoishi/master/screenshot/arcadia.png) | ||
## 注意事项 | ||
> 使用前在 [yjai](http://open.yjai.art/openai-painting) 中获取apikey及apisecret | ||
对于部署者行为及所产生的任何纠纷, Koishi 及 koishi-plugin-arcadia 概不负责。 | ||
如果有更多文本内容想要修改,可以在本地化中修改 zh 内容 | ||
发送arcadia.style,即可切换风格 | ||
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# 更新日志 | ||
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## v1.0.0 | ||
> | ||
正式版 | ||
新增引擎切换,积分查询,任务查询,输出模式切换 | ||
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## v0.1.3 | ||
> | ||
修复无法自动发送图片bug | ||
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## v0.1.2 | ||
> | ||
修复未知错误,增加风格 | ||
"梵高", | ||
'托马斯·科尔', | ||
'赛博朋克', | ||
'中国画', | ||
'蒸汽波', | ||
'莫奈', | ||
'二次元色彩大师', | ||
'经典动漫', | ||
'油画' | ||
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## v0.1.1 | ||
> | ||
能跑了 | ||
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## 感谢inisis佬对插件的支持 |
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# koishi-plugin-artwise | ||
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[![npm](https://img.shields.io/npm/v/koishi-plugin-artwise?style=flat-square)](https://www.npmjs.com/package/koishi-plugin-artwise) | ||
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知数云接口 | ||
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![alt 示例](https://raw.githubusercontent.com/initialencounter/mykoishi/master/screenshot/artwise.png) | ||
> 使用前在 知数云 中获取token | ||
对于部署者行为及所产生的任何纠纷, Koishi 及 koishi-plugin-artwise 概不负责。 | ||
## 使用方法 | ||
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| 功能 | 指令 | | ||
| ---- | ---- | | ||
| midjourney | mj | | ||
| ChatGPT 4 | mai | | ||
| ChatGPT 3.5 | wai | | ||
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## 问题反馈 | ||
* QQ群:399899914 | ||
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* 小伙伴如果遇到问题或者有新的想法,欢迎到[这里](https://github.com/initialencounter/mykoishi/issues)反馈哦~ | ||
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## 更新日志 | ||
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- v0.0.2 | ||
- 新增mj失败后自动重试 |
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