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

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use MoYoYoTech/Translator 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/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 serve -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 Desktop

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 serve -hf MoYoYoTech/Translator:Q5_0

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/Translator:Q5_0"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

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

Hermes Agent

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 serve -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

Atomic Chat

OpenClaw

How to use MoYoYoTech/Translator with OpenClaw:

Start the llama.cpp server

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

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/Translator:Q5_0" \
  --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"

daihui.zhang commited on Apr 22, 2025

Commit

269051f

1 Parent(s): c2e494d

update pipelines launch wait

Browse files

Files changed (1) hide show

transcribe/translatepipes.py +5 -8

transcribe/translatepipes.py CHANGED Viewed

@@ -6,7 +6,7 @@ class TranslatePipes:
         # self.whisper_input_q = mp.Queue()
         # self.translate_input_q = mp.Queue()
         # self.result_queue = mp.Queue()
         # whisper 转录
         self._whisper_pipe_en = self._launch_process(WhisperPipe())
         self._whisper_pipe_zh = self._launch_process(WhisperChinese())
@@ -18,22 +18,19 @@ class TranslatePipes:
         self._translate_7b_pipe = self._launch_process(Translate7BPipe())
         # vad
         # self._vad_pipe = self._launch_process(VadPipe())
     # def reset(self):
     #     self._vad_pipe.reset()
     def _launch_process(self, process_obj):
         process_obj.daemon = True
         process_obj.start()
         return process_obj
     def wait_ready(self):
-        self._whisper_pipe_zh.wait()
-        self._funasr_pipe.wait()
-        self._whisper_pipe_en.wait()
-        # self._translate_pipe.wait()
-        # self._vad_pipe.wait()
-        self._translate_7b_pipe.wait()
     def translate(self, text, src_lang, dst_lang) -> MetaItem:
         item = MetaItem(

         # self.whisper_input_q = mp.Queue()
         # self.translate_input_q = mp.Queue()
         # self.result_queue = mp.Queue()
+        self._process = []
         # whisper 转录
         self._whisper_pipe_en = self._launch_process(WhisperPipe())
         self._whisper_pipe_zh = self._launch_process(WhisperChinese())
         self._translate_7b_pipe = self._launch_process(Translate7BPipe())
         # vad
         # self._vad_pipe = self._launch_process(VadPipe())
     # def reset(self):
     #     self._vad_pipe.reset()
     def _launch_process(self, process_obj):
         process_obj.daemon = True
         process_obj.start()
+        self._process.append(process_obj)
         return process_obj
     def wait_ready(self):
+        for p in self._process:
+            p.wait()
     def translate(self, text, src_lang, dst_lang) -> MetaItem:
         item = MetaItem(