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")
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 Jul 1, 2025

Commit

941bf07

1 Parent(s): e0f42b2

Refactor LlamaCpp initialization to simplify parameter handling and remove unused callback manager

Browse files

Files changed (2) hide show

src/voice_dialogue/config/llm_config.py +2 -0
src/voice_dialogue/services/text/processor.py +1 -13

src/voice_dialogue/config/llm_config.py CHANGED Viewed

@@ -19,6 +19,8 @@ def get_llm_model_params() -> Dict[str, Any]:
     # 基础模型参数
     model_params = {
         'streaming': True,
         'temperature': 0.7,
         'top_p': 0.9,
         'top_k': 20,

     # 基础模型参数
     model_params = {
         'streaming': True,
+        'n_gpu_layers': -1,
+        'n_batch': 1024,
         'temperature': 0.7,
         'top_p': 0.9,
         'top_k': 20,

src/voice_dialogue/services/text/processor.py CHANGED Viewed

@@ -2,7 +2,6 @@ import pathlib
 import typing
 from langchain_community.chat_models.llamacpp import ChatLlamaCpp
-from langchain_core.callbacks import StreamingStdOutCallbackHandler, CallbackManager
 from langchain_core.messages import SystemMessage
 from langchain_core.prompts import (
     ChatPromptTemplate, MessagesPlaceholder, HumanMessagePromptTemplate
@@ -22,20 +21,9 @@ def create_langchain_chat_llamacpp_instance(
     logger.info(">>>>>>> Initializing LlamaCpp Langchain instance...")
     model_path = pathlib.Path(local_model_path)
-    callback_manager = CallbackManager([StreamingStdOutCallbackHandler()])
     llamacpp_langchain_instance = ChatLlamaCpp(
         model_path=str(model_path),
-        streaming=model_params.get('streaming', True),
-        n_gpu_layers=model_params.get('n_gpu_layers', -1),
-        n_batch=model_params.get('n_batch', 512),
-        n_ctx=model_params.get('n_ctx', 2048),
-        f16_kv=model_params.get('f16_kv', True),
-        temperature=model_params.get('temperature', 0.8),
-        top_k=model_params.get('top_k', 40),
-        top_p=model_params.get('top_p', 0.95),
-        max_tokens=model_params.get('n_predict', 256),
-        # callback_manager=callback_manager,
-        verbose=False
     )
     return llamacpp_langchain_instance

 import typing
 from langchain_community.chat_models.llamacpp import ChatLlamaCpp
 from langchain_core.messages import SystemMessage
 from langchain_core.prompts import (
     ChatPromptTemplate, MessagesPlaceholder, HumanMessagePromptTemplate
     logger.info(">>>>>>> Initializing LlamaCpp Langchain instance...")
     model_path = pathlib.Path(local_model_path)
     llamacpp_langchain_instance = ChatLlamaCpp(
         model_path=str(model_path),
+        **model_params
     )
     return llamacpp_langchain_instance