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 ·
4895dc2
1
Parent(s): 037e5ae
Remove `voice_schemas.py` and refactor schema imports for TTS and ASR modules in `__init__.py`
Browse files
src/voice_dialogue/api/schemas/__init__.py
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from .system_schemas import (
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SystemStatusResponse, SystemResponse
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from .
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)
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__all__ = [
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"
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"
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]
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from .asr_schemas import (
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SupportedLanguagesResponse,
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ASRInstanceRequest,
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ASRInstanceResponse
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)
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from .system_schemas import (
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SystemStatusResponse, SystemResponse
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)
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from .tts_schemas import (
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TTSModelInfo,
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TTSModelListResponse,
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TTSModelLoadRequest,
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TTSModelLoadResponse,
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TTSModelStatusResponse,
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TTSModelDeleteResponse,
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generate_model_id
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)
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__all__ = [
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# System schemas
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"SystemStatusResponse",
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"SystemResponse",
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# ASR schemas
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"SupportedLanguagesResponse",
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"ASRInstanceRequest",
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"ASRInstanceResponse",
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# TTS schemas
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"TTSModelInfo",
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"TTSModelListResponse",
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"TTSModelLoadRequest",
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"TTSModelLoadResponse",
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"TTSModelStatusResponse",
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"TTSModelDeleteResponse",
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"generate_model_id"
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]
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src/voice_dialogue/api/schemas/voice_schemas.py
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from datetime import datetime
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from typing import Optional, Literal
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from pydantic import BaseModel, Field
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class VoiceInput(BaseModel):
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"""语音输入请求模式"""
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audio_data: str = Field(..., description="Base64编码的音频数据")
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language: Literal['zh', 'en'] = Field(default='zh', description="语音语言")
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class TextInput(BaseModel):
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"""文本输入请求模式"""
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text: str = Field(..., description="输入文本", min_length=1, max_length=1000)
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language: Literal['zh', 'en'] = Field(default='zh', description="文本语言")
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class VoiceResponse(BaseModel):
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"""语音响应模式"""
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transcribed_text: Optional[str] = Field(None, description="转录的文本")
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generated_text: str = Field(..., description="生成的回答文本")
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audio_data: str = Field(..., description="Base64编码的音频响应")
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processing_time: float = Field(..., description="处理时间(秒)")
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timestamp: datetime = Field(default_factory=datetime.now, description="响应时间戳")
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class TTSRequest(BaseModel):
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"""文本转语音请求模式"""
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text: str = Field(..., description="要转换的文本", min_length=1, max_length=1000)
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speaker: str = Field(default='沈逸', description="语音角色")
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class TTSResponse(BaseModel):
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"""文本转语音响应模式"""
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audio_data: str = Field(..., description="Base64编码的音频数据")
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duration: float = Field(..., description="音频时长(秒)")
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class ASRRequest(BaseModel):
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"""语音识别请求模式"""
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audio_data: str = Field(..., description="Base64编码的音频数据")
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language: Literal['zh', 'en'] = Field(default='zh', description="语音语言")
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class ASRResponse(BaseModel):
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"""语音识别响应模式"""
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transcribed_text: str = Field(..., description="识别出的文本")
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confidence: float = Field(..., description="识别置信度")
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