Instructions to use webbigdata/VoiceCore_gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use webbigdata/VoiceCore_gguf with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf webbigdata/VoiceCore_gguf:BF16 # Run inference directly in the terminal: llama cli -hf webbigdata/VoiceCore_gguf:BF16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf webbigdata/VoiceCore_gguf:BF16 # Run inference directly in the terminal: llama cli -hf webbigdata/VoiceCore_gguf:BF16
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf webbigdata/VoiceCore_gguf:BF16 # Run inference directly in the terminal: ./llama-cli -hf webbigdata/VoiceCore_gguf:BF16
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf webbigdata/VoiceCore_gguf:BF16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf webbigdata/VoiceCore_gguf:BF16
Use Docker
docker model run hf.co/webbigdata/VoiceCore_gguf:BF16
- LM Studio
- Jan
- Ollama
How to use webbigdata/VoiceCore_gguf with Ollama:
ollama run hf.co/webbigdata/VoiceCore_gguf:BF16
- Unsloth Desktop
- Docker Model Runner
How to use webbigdata/VoiceCore_gguf with Docker Model Runner:
docker model run hf.co/webbigdata/VoiceCore_gguf:BF16
- Lemonade
How to use webbigdata/VoiceCore_gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull webbigdata/VoiceCore_gguf:BF16
Run and chat with the model
lemonade run user.VoiceCore_gguf-BF16
List all available models
lemonade list
- Atomic Chat

- Xet hash:
- 96c1fc8f383d8fdf5696e7caaa971d6da8fb4c40ce5dea21edafb1a82c2a5c79
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- 207 kB
- SHA256:
- 74444bcd09dea1b5602de77a58c7fde694d23aedc04b4006e3b498b74573abfb
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