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"

liumaolin commited on Jun 23, 2025

Commit

b2c10c8

1 Parent(s): bdc3b7b

Refactor `TestLLMDialogue` to use dynamic LLM model parameters

Browse files

- Replace hardcoded `model_params` with `get_llm_model_params` from `llm_config.py`.
- Update imports to reflect changes in the configuration structure.

Files changed (1) hide show

tests/test_llm_dialogue.py +3 -12

tests/test_llm_dialogue.py CHANGED Viewed

@@ -7,7 +7,8 @@ from langchain_core.messages import SystemMessage
 from langchain_core.prompts import ChatPromptTemplate, HumanMessagePromptTemplate, MessagesPlaceholder
 from langchain_core.runnables.history import RunnableWithMessageHistory
-from config import paths
 CHINESE_SYSTEM_PROMPT = (
     "你是善于模拟真实的思考过程的AI助手。"
@@ -29,17 +30,7 @@ ENGLISH_SYSTEM_PROMPT = (
 class TestLLMDialogue(unittest.TestCase):
     def setUp(self):
-        model_params = {
-            'n_ctx': 32768,
-            'temperature': 0.7,
-            'top_p': 0.9,
-            'top_k': 20,
-            'model_kwargs': {
-                'mini_p': 0,
-                'presence_penalty': 1.5
-            },
-            'verbose': False
-        }
         self.history_store = {}
         model_path = paths.LLM_MODELS_PATH / 'qwen' / 'Qwen3-8B-Q6_K.gguf'

 from langchain_core.prompts import ChatPromptTemplate, HumanMessagePromptTemplate, MessagesPlaceholder
 from langchain_core.runnables.history import RunnableWithMessageHistory
+from voice_dialogue.config import paths
+from voice_dialogue.config.llm_config import get_llm_model_params
 CHINESE_SYSTEM_PROMPT = (
     "你是善于模拟真实的思考过程的AI助手。"
 class TestLLMDialogue(unittest.TestCase):
     def setUp(self):
+        model_params = get_llm_model_params()
         self.history_store = {}
         model_path = paths.LLM_MODELS_PATH / 'qwen' / 'Qwen3-8B-Q6_K.gguf'