- Libraries
- VoxCPM
How to use ghananlpcommunity/ghana-tts-36k-gguf with VoxCPM:
import soundfile as sf
from voxcpm import VoxCPM
model = VoxCPM.from_pretrained("ghananlpcommunity/ghana-tts-36k-gguf")
wav = model.generate(
text="VoxCPM is an innovative end-to-end TTS model from ModelBest, designed to generate highly expressive speech.",
prompt_wav_path=None, # optional: path to a prompt speech for voice cloning
prompt_text=None, # optional: reference text
cfg_value=2.0, # LM guidance on LocDiT, higher for better adherence to the prompt, but maybe worse
inference_timesteps=10, # LocDiT inference timesteps, higher for better result, lower for fast speed
normalize=True, # enable external TN tool
denoise=True, # enable external Denoise tool
retry_badcase=True, # enable retrying mode for some bad cases (unstoppable)
retry_badcase_max_times=3, # maximum retrying times
retry_badcase_ratio_threshold=6.0, # maximum length restriction for bad case detection (simple but effective), it could be adjusted for slow pace speech
)
sf.write("output.wav", wav, 16000)
print("saved: output.wav") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use ghananlpcommunity/ghana-tts-36k-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 ghananlpcommunity/ghana-tts-36k-gguf:F16
# Run inference directly in the terminal:
llama cli -hf ghananlpcommunity/ghana-tts-36k-gguf:F16
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf ghananlpcommunity/ghana-tts-36k-gguf:F16
# Run inference directly in the terminal:
llama cli -hf ghananlpcommunity/ghana-tts-36k-gguf:F16
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 ghananlpcommunity/ghana-tts-36k-gguf:F16
# Run inference directly in the terminal:
./llama-cli -hf ghananlpcommunity/ghana-tts-36k-gguf:F16
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 ghananlpcommunity/ghana-tts-36k-gguf:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf ghananlpcommunity/ghana-tts-36k-gguf:F16
Use Docker
docker model run hf.co/ghananlpcommunity/ghana-tts-36k-gguf:F16
- LM Studio
- Jan
- Ollama
How to use ghananlpcommunity/ghana-tts-36k-gguf with Ollama:
ollama run hf.co/ghananlpcommunity/ghana-tts-36k-gguf:F16
- Unsloth Studio
How to use ghananlpcommunity/ghana-tts-36k-gguf with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for ghananlpcommunity/ghana-tts-36k-gguf to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for ghananlpcommunity/ghana-tts-36k-gguf to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for ghananlpcommunity/ghana-tts-36k-gguf to start chatting
- Docker Model Runner
How to use ghananlpcommunity/ghana-tts-36k-gguf with Docker Model Runner:
docker model run hf.co/ghananlpcommunity/ghana-tts-36k-gguf:F16
- Lemonade
How to use ghananlpcommunity/ghana-tts-36k-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/
lemonade pull ghananlpcommunity/ghana-tts-36k-gguf:F16
Run and chat with the model
lemonade run user.ghana-tts-36k-gguf-F16
List all available models
lemonade list
- Atomic Chat
