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", dtype="auto") - llama-cpp-python
How to use MoYoYoTech/VoiceDialogue with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="MoYoYoTech/VoiceDialogue", filename="assets/models/llm/qwen/Qwen3-8B-Q6_K.gguf", )
llm.create_chat_completion( messages = "\"The answer to the universe is 42\"" )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use MoYoYoTech/VoiceDialogue with llama.cpp:
Install from brew
brew install llama.cpp # 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
Install from WinGet (Windows)
winget install llama.cpp # 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
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 new
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 new
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-server -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-server -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
- 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
liumaolin commited on
Commit ·
8acaad0
1
Parent(s): 40186e2
Refactor ASR manager: remove `_get_asr_supported_languages`, replace static language mapping with `supported_langs` attribute, and update dynamic module import to use `importlib.util` for improved maintainability.
Browse files
src/VoiceDialogue/services/speech/asr/manager.py
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import inspect
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import logging
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import re
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)
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print("\n")
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def _get_asr_supported_languages(self, asr_key: str) -> List[str]:
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"""获取特定ASR引擎支持的语言列表"""
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# 根据ASR类型返回支持的语言
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language_mapping = {
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'funasr': ['zh', 'auto'],
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'whisper': ['en', 'zh', 'auto'],
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}
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return language_mapping.get(asr_key, ['auto'])
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def register(self, register_table_key: str, key: str = None) -> callable:
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"""装饰器,用于注册ASR类"""
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self._language_to_asr_mapping = {
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'zh': 'funasr', # 中文优先使用FunASR
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'en': 'whisper', # 英文优先使用Whisper
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'auto': 'whisper', # 自动检测默认使用Whisper
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}
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def create_asr(self, language: Literal['auto', 'zh', 'en']) -> ASRInterface:
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"""
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supported_languages = {}
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for asr_key in asr_tables.asr_classes.
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try:
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except Exception as e:
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logging.warning(f"获取ASR引擎 '{asr_key}' 支持的语言失败: {e}")
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supported_languages[asr_key] = ['unknown']
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module_name = py_file.stem
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try:
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# 动态导入模块
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logging.info(f"Successfully imported ASR module: {module_name}")
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except ImportError as e:
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logging.warning(f"Failed to import ASR module {module_name}: {e}")
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import importlib.util
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import inspect
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import logging
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import re
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)
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print("\n")
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def register(self, register_table_key: str, key: str = None) -> callable:
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"""装饰器,用于注册ASR类"""
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self._language_to_asr_mapping = {
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'zh': 'funasr', # 中文优先使用FunASR
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'en': 'whisper', # 英文优先使用Whisper
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# 'auto': 'whisper', # 自动检测默认使用Whisper
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}
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def create_asr(self, language: Literal['auto', 'zh', 'en']) -> ASRInterface:
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"""
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supported_languages = {}
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for asr_key, asr_class in asr_tables.asr_classes.items():
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try:
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supported_languages[asr_key] = asr_class.supported_langs
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# languages = asr_tables._get_asr_supported_languages(asr_key)
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# supported_languages[asr_key] = languages
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except Exception as e:
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logging.warning(f"获取ASR引擎 '{asr_key}' 支持的语言失败: {e}")
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supported_languages[asr_key] = ['unknown']
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module_name = py_file.stem
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try:
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# 动态导入模块
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spec = importlib.util.spec_from_file_location(
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f".models.{module_name}",
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py_file
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)
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module = importlib.util.module_from_spec(spec)
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spec.loader.exec_module(module)
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logging.info(f"Successfully imported ASR module: {module_name}")
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except ImportError as e:
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logging.warning(f"Failed to import ASR module {module_name}: {e}")
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src/VoiceDialogue/services/speech/asr/models/whisper.py
CHANGED
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@asr_tables.register('asr_classes', 'whisper')
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class WhisperCppClient(ASRInterface):
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"""Whisper C++ API客户端"""
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supported_langs = ['en', 'zh',
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def __init__(self):
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super().__init__()
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@asr_tables.register('asr_classes', 'whisper')
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class WhisperCppClient(ASRInterface):
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"""Whisper C++ API客户端"""
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supported_langs = ['en', 'zh', ]
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def __init__(self):
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super().__init__()
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