Instructions to use MoYoYoTech/VoiceDialogue with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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")

# pip install -U transformers accelerate
# 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

Build from source code

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -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

Llama new
LM Studio
Jan
Ollama
How to use MoYoYoTech/VoiceDialogue with Ollama:
```
ollama run hf.co/MoYoYoTech/VoiceDialogue:Q6_K
```
Unsloth Desktop

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 @earendil-works/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

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

Hermes Agent

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

OpenClaw

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"

VoiceDialogue / src /voice_dialogue /services /utils.py

liumaolin

新增Mixin类以增强语音任务处理功能

2ebe57f over 1 year ago

Raw History Blame

1.07 kB

import re

import librosa
import numpy as np

from voice_dialogue.utils.logger import logger


def has_no_words(text: str) -> bool:
    """
    检查文本是否不包含任何单词（字母、数字或中文字符）。
    如果文本只包含标点、空格等符号，则返回 True。
    """
    if not text:
        return True
    # 搜索任何字母、数字或中文字符
    if re.search(r'[\u4e00-\u9fa5a-zA-Z0-9]', text):
        return False
    return True


def normalize_audio_frame(data: bytes) -> 'np.ndarray':
    """
    将 int16 格式的音频字节数据转换为 [-1.0, 1.0] 范围的 numpy 浮点数组。
    """
    return np.frombuffer(data, dtype=np.int16).astype(np.float32) / np.iinfo(np.int16).max


def calculate_audio_duration(audio_data: 'np.ndarray', sample_rate: int = 16000) -> float:
    """
    计算音频时长（秒）。
    """
    try:
        return librosa.get_duration(y=audio_data, sr=sample_rate)
    except Exception as e:
        logger.error(f"计算音频时长时发生错误: {e}")
        return 0.0

	import re

	import librosa
	import numpy as np

	from voice_dialogue.utils.logger import logger


	def has_no_words(text: str) -> bool:
	"""
	检查文本是否不包含任何单词（字母、数字或中文字符）。
	如果文本只包含标点、空格等符号，则返回 True。
	"""
	if not text:
	return True
	# 搜索任何字母、数字或中文字符
	if re.search(r'[\u4e00-\u9fa5a-zA-Z0-9]', text):
	return False
	return True


	def normalize_audio_frame(data: bytes) -> 'np.ndarray':
	"""
	将 int16 格式的音频字节数据转换为 [-1.0, 1.0] 范围的 numpy 浮点数组。
	"""
	return np.frombuffer(data, dtype=np.int16).astype(np.float32) / np.iinfo(np.int16).max


	def calculate_audio_duration(audio_data: 'np.ndarray', sample_rate: int = 16000) -> float:
	"""
	计算音频时长（秒）。
	"""
	try:
	return librosa.get_duration(y=audio_data, sr=sample_rate)
	except Exception as e:
	logger.error(f"计算音频时长时发生错误: {e}")
	return 0.0