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

Libraries

How to use MoYoYoTech/Translator with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="MoYoYoTech/Translator",
	filename="moyoyo_asr_models/qwen2.5-1.5b-instruct-q5_0.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use MoYoYoTech/Translator with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf MoYoYoTech/Translator:Q5_0
# Run inference directly in the terminal:
llama-cli -hf MoYoYoTech/Translator:Q5_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf MoYoYoTech/Translator:Q5_0
# Run inference directly in the terminal:
llama-cli -hf MoYoYoTech/Translator:Q5_0

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/Translator:Q5_0
# Run inference directly in the terminal:
./llama-cli -hf MoYoYoTech/Translator:Q5_0

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/Translator:Q5_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf MoYoYoTech/Translator:Q5_0

Use Docker

docker model run hf.co/MoYoYoTech/Translator:Q5_0

LM Studio
Jan
Ollama
How to use MoYoYoTech/Translator with Ollama:
```
ollama run hf.co/MoYoYoTech/Translator:Q5_0
```

Unsloth Studio

How to use MoYoYoTech/Translator 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/Translator 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/Translator to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for MoYoYoTech/Translator to start chatting

How to use MoYoYoTech/Translator with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf MoYoYoTech/Translator:Q5_0

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/Translator:Q5_0"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use MoYoYoTech/Translator 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/Translator:Q5_0

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/Translator:Q5_0

Run Hermes

hermes

Docker Model Runner
How to use MoYoYoTech/Translator with Docker Model Runner:
```
docker model run hf.co/MoYoYoTech/Translator:Q5_0
```

Lemonade

How to use MoYoYoTech/Translator with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull MoYoYoTech/Translator:Q5_0

Run and chat with the model

lemonade run user.Translator-Q5_0

List all available models

lemonade list

daihui.zhang commited on Apr 16, 2025

Commit

dc4b6b8

1 Parent(s): b9ad81c

update readme

Browse files

Files changed (1) hide show

README.md +9 -3

README.md CHANGED Viewed

@@ -5,6 +5,12 @@ license: mit
 ## 环境安装
 ### Python 基本环境
 > 1. 使用以下命令安装所需的 Python 库：
    ```bash
@@ -18,7 +24,7 @@ license: mit
    ```
 > 2. 切换到特定的提交版本：
    ```bash
-   git checkout d43237bd75076615349004270a721e3ebe1deabb
    ```
 > 3. 安装 WhisperCPP，确保启用 CoreML 支持：
    ```bash
@@ -32,11 +38,11 @@ license: mit
    ```
 > 2. 切换到特定的提交版本：
    ```bash
-   cd llama-cpp-python && git checkout 0580cf273debf4a7f2efcdfd5ef092ff5cedf9b0 && cd vendor/llama.cpp && git checkout ecebbd292d741ac084cf248146b2cfb17002aa1d
    ```
 > 3. 使用以下命令安装 Llama-cpp-python，确保启用 Metal 支持：
    ```bash
-   CMAKE_ARGS="-DGGML_METAL=on" pip install .
    ```
 ## 运行

 ## 环境安装
+## 系统环境
+> 1. 安装portaudio环境
+```bash
+   brew install portaudio
+```
 ### Python 基本环境
 > 1. 使用以下命令安装所需的 Python 库：
    ```bash
    ```
 > 2. 切换到特定的提交版本：
    ```bash
+   cd pywhispercpp && git checkout d43237bd75076615349004270a721e3ebe1deabb
    ```
 > 3. 安装 WhisperCPP，确保启用 CoreML 支持：
    ```bash
    ```
 > 2. 切换到特定的提交版本：
    ```bash
+   cd llama-cpp-python && git checkout 0580cf273debf4a7f2efcdfd5ef092ff5cedf9b0 && cd vendor/llama.cpp && git checkout ecebbd292d741ac084cf248146b2cfb17002aa1d &&   cd ../..
    ```
 > 3. 使用以下命令安装 Llama-cpp-python，确保启用 Metal 支持：
    ```bash
+ CMAKE_ARGS="-DGGML_METAL=on" pip install .
    ```
 ## 运行