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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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| .. | ||
| .gitignore | ||
| CMakeLists.txt | ||
| README.md | ||
| eleven-labs.py | ||
| gpt-2.cpp | ||
| gpt-2.h | ||
| speak.sh | ||
| talk.cpp | ||
README.md
talk
Talk with an Artificial Intelligence in your terminal
Web version: examples/talk.wasm
Building
The talk 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" executable
make talk
# Run it
./talk -p Santa
GPT-2
To run this, you will need a ggml GPT-2 model: instructions
Alternatively, you can simply download the smallest ggml GPT-2 117M model (240 MB) like this:
wget --quiet --show-progress -O models/ggml-gpt-2-117M.bin https://huggingface.co/ggerganov/ggml/raw/main/ggml-model-gpt-2-117M.bin
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 espeak, but you can use whatever you wish.