Text-to-Speech
Transformers
ONNX
GGUF
Chinese
English
voice-dialogue
speech-recognition
large-language-model
asr
tts
llm
chinese
english
real-time
conversational
Instructions to use MoYoYoTech/VoiceDialogue with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MoYoYoTech/VoiceDialogue with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="MoYoYoTech/VoiceDialogue") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MoYoYoTech/VoiceDialogue", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use MoYoYoTech/VoiceDialogue 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 MoYoYoTech/VoiceDialogue:Q6_K # Run inference directly in the terminal: llama cli -hf MoYoYoTech/VoiceDialogue:Q6_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf MoYoYoTech/VoiceDialogue:Q6_K # Run inference directly in the terminal: llama cli -hf MoYoYoTech/VoiceDialogue:Q6_K
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 MoYoYoTech/VoiceDialogue:Q6_K # Run inference directly in the terminal: ./llama-cli -hf MoYoYoTech/VoiceDialogue:Q6_K
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 MoYoYoTech/VoiceDialogue:Q6_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf MoYoYoTech/VoiceDialogue:Q6_K
Use Docker
docker model run hf.co/MoYoYoTech/VoiceDialogue:Q6_K
- LM Studio
- Jan
- Ollama
How to use MoYoYoTech/VoiceDialogue with Ollama:
ollama run hf.co/MoYoYoTech/VoiceDialogue:Q6_K
- Unsloth Studio
How to use MoYoYoTech/VoiceDialogue 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 MoYoYoTech/VoiceDialogue 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 MoYoYoTech/VoiceDialogue to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for MoYoYoTech/VoiceDialogue to start chatting
- Pi
How to use MoYoYoTech/VoiceDialogue with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf MoYoYoTech/VoiceDialogue:Q6_K
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "MoYoYoTech/VoiceDialogue:Q6_K" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use MoYoYoTech/VoiceDialogue with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf MoYoYoTech/VoiceDialogue:Q6_K
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default MoYoYoTech/VoiceDialogue:Q6_K
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use MoYoYoTech/VoiceDialogue with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf MoYoYoTech/VoiceDialogue:Q6_K
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "MoYoYoTech/VoiceDialogue:Q6_K" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
- Docker Model Runner
How to use MoYoYoTech/VoiceDialogue with Docker Model Runner:
docker model run hf.co/MoYoYoTech/VoiceDialogue:Q6_K
- Lemonade
How to use MoYoYoTech/VoiceDialogue with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull MoYoYoTech/VoiceDialogue:Q6_K
Run and chat with the model
lemonade run user.VoiceDialogue-Q6_K
List all available models
lemonade list
File size: 3,662 Bytes
84faf7d 511ff0c 7b64dcd 84faf7d 8f823b0 511ff0c 824183a 511ff0c 84faf7d e0f42b2 84faf7d 7b64dcd 8f823b0 511ff0c 8f823b0 afd6c89 e0f42b2 8f823b0 e0f42b2 8f823b0 afd6c89 8f823b0 afd6c89 8f823b0 7b64dcd | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 | import multiprocessing
import os
import sys
import typing
from pathlib import Path
if __name__ == '__main__':
if hasattr(sys, '_voice_dialogue_started'):
sys.exit(0)
sys._voice_dialogue_started = True
# 设置multiprocessing启动方法为spawn,避免fork问题
if hasattr(multiprocessing, 'set_start_method'):
try:
multiprocessing.set_start_method('spawn', force=True)
except RuntimeError:
pass
# Pyinstaller 多进程支持
multiprocessing.freeze_support()
# 禁用各种可能导致多进程问题的并行处理
os.environ.update({
"TOKENIZERS_PARALLELISM": "false",
# "OMP_NUM_THREADS": "1",
# "MKL_NUM_THREADS": "1",
# "NUMEXPR_NUM_THREADS": "1",
# "OPENBLAS_NUM_THREADS": "1",
# "VECLIB_MAXIMUM_THREADS": "1",
# "BLIS_NUM_THREADS": "1",
# # 禁用huggingface的多进程
# "HF_HUB_DISABLE_PROGRESS_BARS": "1",
# "TRANSFORMERS_NO_ADVISORY_WARNINGS": "1",
# # 禁用torch的多进程
# "TORCH_NUM_THREADS": "1",
# "PYTORCH_JIT": "0",
# # 禁用joblib的loky后端,使用threading
# "JOBLIB_START_METHOD": "threading",
# "SKLEARN_JOBLIB_START_METHOD": "threading",
})
HERE = Path(__file__).parent
lib_path = HERE / "src"
if lib_path.exists() and lib_path.as_posix() not in sys.path:
sys.path.insert(0, lib_path.as_posix())
from voice_dialogue.core.launcher import launch_system
from voice_dialogue.core.constants import set_debug_mode
from voice_dialogue.cli.args import create_argument_parser
from voice_dialogue.api.server import launch_api_server
language: typing.Literal['zh', 'en'] = 'en'
def main():
"""
主程序入口函数
根据命令行参数选择启动模式:
- cli: 启动命令行语音对话系统
- api: 启动HTTP API服务器
"""
parser = create_argument_parser()
args = parser.parse_args()
# 列出音频输入设备后退出
if getattr(args, 'list_audio_devices', False):
from voice_dialogue.audio.devices import list_input_devices
devices = list_input_devices()
print(f"\n可用音频输入设备 ({len(devices)}):")
print(f"{'索引':>4} {'通道':>4} {'采样率':>7} {'默认':>4} 名称")
for d in devices:
default_mark = '✓' if d['is_default'] else ''
print(f"{d['index']:>4} {d['max_input_channels']:>4} "
f"{d['default_sample_rate']:>7} {default_mark:>4} {d['name']}")
print("\n使用 --input-device <索引> 选择设备。")
sys.exit(0)
set_debug_mode(args.debug)
print(f"""
{"=" * 80}
VoiceDialogue - 语音对话系统
{"=" * 80}
运行模式: {args.mode.upper()}
调试模式: {'启用' if args.debug else '禁用'}
{"=" * 80}
""")
try:
if args.mode == 'cli':
print(f"语言设置: {args.language}")
print(f"说话人: {args.speaker}")
if args.input_device is not None:
print(f"输入设备索引: {args.input_device}")
print("正在启动命令行语音对话系统...")
launch_system(args.language, args.speaker, args.disable_echo_cancellation, args.input_device)
elif args.mode == 'api':
launch_api_server(
host=args.host,
port=args.port,
reload=args.reload
)
except KeyboardInterrupt:
print("\n程序被用户中断")
except Exception as e:
print(f"程序运行出错: {e}")
raise
if __name__ == '__main__':
main()
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