license: cc-by-sa-4.0
language:
- en
- hi
base_model:
- 11mlabs/indri-0.1-124m-tts
pipeline_tag: text-to-speech
Indri GGUF Inference
Refer to the original model and more details here.
This guide will help in running Indri models on CPU in GGUF format.
Step 1: Build llama.cpp
To run the inference locally, you need to build llama.cpp project. The updated guide to do so can be found here.
git clone https://github.com/ggerganov/llama.cpp
cd llama.cpp
cmake -B build
cmake --build build --config Release
Step 2: Download the model
Download the GGUF format models from HuggingFace and place them inside llama.cpp/models/.
The models can be found here.
Once the model is placed inside the directory, run the llama-cpp server from inside the llama.cpp directory
# For F16 model, update for different quantization accordingly
./build/bin/llama-server -m /indri-0.1-124M-tts-F16.gguf --samplers 'top_k;temperature' --top_k 15
Refer here if you are facing issues in running the llama-server locally.
Step 3: Run the inference script
Clone the GitHub repository:
git clone https://github.com/cmeraki/indri.git
cd indri
python -m src.tts_gguf --text 'hi my name is Indri' --speaker '[spkr_63]' --out out.wav
Speakers are available here.
You can also run an inference server
pip install -r requirements.txt
# Install ffmpeg (for Mac/Windows, refer here: https://www.ffmpeg.org/download.html)
sudo apt update -y
sudo apt upgrade -y
sudo apt install ffmpeg -y
python -m server_ggpuf
Redirect to http://localhost:8000/docs to see the API documentation and test the service.
We are working on making this process more straightforward. Stay tuned for updates!