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 22, 2025

Commit

1bf4992

1 Parent(s): 3a0633a

fix words missing

Browse files

Files changed (4) hide show

pyproject.toml +1 -0
requirements.txt +1 -0
transcribe/whisper_llm_serve.py +5 -1
uv.lock +0 -0

pyproject.toml CHANGED Viewed

@@ -7,6 +7,7 @@ requires-python = ">=3.11"
 dependencies = [
     "av>=14.2.0",
     "fastapi>=0.115.12",
     "librosa>=0.11.0",
     "numpy>=2.1.3",
     "onnxruntime>=1.21.0",

 dependencies = [
     "av>=14.2.0",
     "fastapi>=0.115.12",
+    "funasr>=1.2.6",
     "librosa>=0.11.0",
     "numpy>=2.1.3",
     "onnxruntime>=1.21.0",

requirements.txt CHANGED Viewed

@@ -184,3 +184,4 @@ websockets==15.0.1
     # via trans (pyproject.toml)
 wordninja==2.0.0
     # via trans (pyproject.toml)

     # via trans (pyproject.toml)
 wordninja==2.0.0
     # via trans (pyproject.toml)
+funasr==1.2.6

transcribe/whisper_llm_serve.py CHANGED Viewed

@@ -180,9 +180,13 @@ class WhisperTranscriptionService:
         while not self._translate_thread_stop.is_set():
             audio_buffer = self._vad_frame_queue.get()
-            if audio_buffer is None or len(audio_buffer) < int(self.sample_rate):
                 time.sleep(0.2)
                 continue
             logger.debug(f"audio buffer size: {len(audio_buffer) / self.sample_rate:.2f}s")
             # try:

         while not self._translate_thread_stop.is_set():
             audio_buffer = self._vad_frame_queue.get()
+            if audio_buffer is None:
                 time.sleep(0.2)
                 continue
+            if len(audio_buffer) < int(self.sample_rate):
+                silence_audio = np.zeros(self.sample_rate, dtype=np.float32)
+                silence_audio[-len(audio_buffer):] = audio_buffer
+                audio_buffer = silence_audio
             logger.debug(f"audio buffer size: {len(audio_buffer) / self.sample_rate:.2f}s")
             # try:

uv.lock CHANGED Viewed

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