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* whisper : add integer quantization support * examples : add common-ggml + prepare to add "quantize" tool * whisper : quantization tool ready * whisper : fix F32 support * whisper : try to fix shared lib linkage * wasm : update quantized models to Q5 * bench.wasm : remove "medium" button * bench.wasm : fix custom model button * ggml : add Q5_0 and Q5_1 WASM SIMD * wasm : add quantized models to all WASM examples * wasm : bump DB version number to 2 * talk-llama : update example to latest llama.cpp * node : increase test timeout to 10s * readme : add information for model quantization * wasm : add links to other examples |
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.. | ||
prompts | ||
.gitignore | ||
CMakeLists.txt | ||
eleven-labs.py | ||
llama-util.h | ||
llama.cpp | ||
llama.h | ||
README.md | ||
speak.sh | ||
talk-llama.cpp |
talk-llama
Talk with an LLaMA AI in your terminal
Building
The talk-llama
tool depends on SDL2 library to capture audio from the microphone. You can build it like this:
# Install SDL2 on Linux
sudo apt-get install libsdl2-dev
# Install SDL2 on Mac OS
brew install sdl2
# Build the "talk-llama" executable
make talk-llama
# Run it
./talk-llama -mw ./models/ggml-small.en.bin -ml ../llama.cpp/models/13B/ggml-model-q4_0.bin -p "Georgi" -t 8
- The
-mw
argument specifies the Whisper model that you would like to use. Recommendedbase
orsmall
for real-time experience - The
-ml
argument specifies the LLaMA model that you would like to use. Read the instructions in https://github.com/ggerganov/llama.cpp for information about how to obtain aggml
compatible LLaMA model
TTS
For best experience, this example needs a TTS tool to convert the generated text responses to voice.
You can use any TTS engine that you would like - simply edit the speak.sh script to your needs.
By default, it is configured to use MacOS's say
, but you can use whatever you wish.
Discussion
If you have any feedback, please let "us" know in the following discussion: https://github.com/ggerganov/whisper.cpp/discussions/672?converting=1