From 73ae41091689cd904ff2e16bbdc40a53b5a01bff Mon Sep 17 00:00:00 2001 From: ortizcruz Date: Fri, 22 Sep 2023 14:21:28 +0200 Subject: [PATCH] update --- README.md | 23 ++++++++++++++++++++--- 1 file changed, 20 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 635d32b..33cd38c 100644 --- a/README.md +++ b/README.md @@ -25,8 +25,10 @@ The following command will pull and install the latest commit from this reposito pip install git+https://github.com/JSchmie/autotranscript.git -- **Python version**: Python 3.9 +- **Python version**: Python 3.8 - **PyTorch version**: Python 1.11.0 +- **CUDA version**: Cuda-toolkit 11.3.1 + Important: For the `Pyannote` model you need to be granted access in Hugging Face. Check the [Pyannote model page](https://huggingface.co/pyannote/speaker-diarization) to get access to the model. @@ -41,6 +43,10 @@ We've developed ScrAIbe with several access points to cater to diverse user need It enables full control over the functionalities as well as process customization. +Some usage examples: + +- Usage of `AutoTranscribe`, core of the transcription system, for performing trancription and diarization of audio files. + ```python from scraibe import AutoTranscribe @@ -79,15 +85,26 @@ Run the following to view all available options: After you have installed Docker, you can execute the following commands in the terminal. ``` -sudo docker build . --build-arg="hf_token=[enter your HuggingFace token] " --no-cache -t [image name] +sudo docker build . --build-arg="hf_token=[enter your HuggingFace token] " -t [image name] -sudo docker run --rm -it -p 7860:7860 --name [container name][image name] --hf_token [enter your HuggingFace token] --start_server +sudo docker run -it -p 7860:7860 --name [container name][image name] --hf_token [enter your HuggingFace token] --start_server ``` +- `-p`: Flag for connecting the container interal port to the port on your local machine. +- `--hf_token`: Flag for entering your personal HuggingFace token in the container. +- `--start_server`: Command to start the Gradio App. + Then click the following link to run the app: http://0.0.0.0:7860 +- Enabling GPU usage + +``` +sudo docker run -it -p 7860:7860 --gpus 'all,capabilities=utility' --name [container name][image name] --hf_token [enter your HuggingFace token] --start_server +``` +For further guidance check: https://blog.roboflow.com/use-the-gpu-in-docker/ + ## Documentation