: C++ string 在main函数中加入:(一般是放在main函数的头几行,越早了解用户的需求越好么^_^) google::ParseCommandLineFlags(&argc, &argv, true); argc和argv想必大家都很清楚了,说明以下第三个参数的作用: 如果设为true,则该函数处理完成后,argv中只保留argv[0],argc会被设置为1。 如果为false,则argv和...
開頭在 Colab 代表執行 Shell 命令。因為官方的 Whisper 有 Commandline 介面,所以執行起來很方便。只是還有一些東西要設定: 點選右上角的連線: 如果有看影片介紹或是實際測試過會知道有沒有用 GPU CUDA 速度會差非常多,所以我們加了--device cuda參數。但也同時要開啟 Colab 執行階段的 GPU。連線後點選顯示 RAM...
其实,不管是用本地GPU跑Whisper的开源模型来转录还是采用OpenAI在线的Whisper API接口进行转录,基本上对于语音或者视频转文本来讲,我们是不是可以结合今天的案例写个爬虫自动抓取YouTube或者其他站点的内容,结合ChatGPT做一些总结分析,然后将结果推送给用户,如果从海量的信息里获取更有价值的内容,AI给我们创造了无限的空间。
GPU execution requires the NVIDIA libraries cuBLAS 11.x and cuDNN 8.x to be installed on the system. Please refer to theCTranslate2 documentation By default the best hardware available is selected for inference. You can use the options--deviceand--device_indexto control manually the selection...
command-0.mp4 On Apple Silicon, the inference runs fully on the GPU via Metal: metal-base-1.mp4 Quick start First clone the repository: git clone https://github.com/ggerganov/whisper.cpp.git Navigate into the directory: cd whisper.cpp ...
whisper_free(ctx); return 0; } 注: whisper支持的模型文件需要自己去下载 whisper.cpp编译可以配置多种类型的增强选项,比如支持CPU/GPU加速,数据计算加速库 whisper.cpp的编译cmake文件做了少量改动,方便集成到项目,具体可参看demo 源码 whispercpp_starter...
(This is also where you can change it from using your gpu to instead use your cpu (performance will vary). Just change “cuda” to “cpu”, then save and exit.)Redo Step 1, and it should say that the Local Whisper Server is started, and skip to Step 4.If it still shows that ...
I'll push an update to have it select Cuda automatically, if available, in the next days. We ran the code on an old 1070 GPU and the transcription time is around a quarter of the lenght of the audio. Just check back in the next days!
CUDA 11.6和CUDA 11.7都是gpu版本的软件,我一开始下载的也是gpu版本的,但是因为我的电脑显卡的显存比较低,运行whisper模型的时候大模型运行不了。为了能运行更大的模型以保证语音识别较高的准确率,我最终只能选择安装cpu版本。 C:\Users\Administrator>pip3 install torch torchvision torchaudio…… Successfully ...
Model flush, for low gpu mem resources Faster-whisper backend Add max-line etc. see (openai's whisper utils.py) Sentence-level segments (nltk toolbox) Improve alignment logic update examples with diarization and word highlighting Subtitle .ass output <- bring this back (removed in v3) ...