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

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/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

Llama new
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 8, 2025

Commit

ded2334

1 Parent(s): df55474

add logging format

Browse files

Files changed (1) hide show

transcribe/whisper_llm_serve.py +4 -2

transcribe/whisper_llm_serve.py CHANGED Viewed

@@ -264,8 +264,9 @@ class PyWhiperCppServe(ServeClientBase):
         transcribe_fut = self._pool.submit(
             PywhisperInference.transcribe, audio_buffer.tobytes(), self.language)
-        log_block("Whisper transcrible time", f"{(time.perf_counter() - start_time):.3f}", "s")
         segments = transcribe_fut.result()
         return segments
     def translate_text(self, text):
@@ -277,8 +278,9 @@ class PyWhiperCppServe(ServeClientBase):
         translate_fut = self._pool.submit(
             PywhisperInference.translate, text, self.language, self.dst_lang)
         log_block("LLM translate time", f"{(time.perf_counter() - start_time):.3f}", "s")
-        return  translate_fut.result()
     def _segments_split(self, segments, audio_buffer: np.ndarray):
         """根据左边第一个标点符号来将序列拆分成 观察段 和 剩余部分"""

         transcribe_fut = self._pool.submit(
             PywhisperInference.transcribe, audio_buffer.tobytes(), self.language)
         segments = transcribe_fut.result()
+        log_block("Whisper transcrible time", f"{(time.perf_counter() - start_time):.3f}", "s")
         return segments
     def translate_text(self, text):
         translate_fut = self._pool.submit(
             PywhisperInference.translate, text, self.language, self.dst_lang)
+        ret =   translate_fut.result()
         log_block("LLM translate time", f"{(time.perf_counter() - start_time):.3f}", "s")
+        return ret
     def _segments_split(self, segments, audio_buffer: np.ndarray):
         """根据左边第一个标点符号来将序列拆分成 观察段 和 剩余部分"""