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ortizcruz
2023-09-22 14:21:28 +02:00
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README.md
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@@ -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