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 Settings

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 8, 2025

Commit

783b899

1 Parent(s): 69bc449

add readme info

Browse files

Files changed (1) hide show

transcribe/whisper_llm_serve.py +2 -6

transcribe/whisper_llm_serve.py CHANGED Viewed

@@ -116,7 +116,7 @@ class PywhisperInference:
     whisper_model = None
     llm_model = None
     vad_model = None
-    init_event = None
     @classmethod
     def initializer(cls, event:mp.Event, warmup=True):
@@ -134,7 +134,7 @@ class PywhisperInference:
         # init llamacpp
         cls.llm_model = QwenTranslator(config.LLM_MODEL_PATH, config.LLM_SYS_PROMPT)
         cls.vad_model = VoiceActivityDetector()
-        cls.init_event = event
         event.set()
@@ -391,10 +391,6 @@ class PyWhiperCppServe(ServeClientBase):
             )
     def send_to_client(self, data:TransResult):
-        # content = {
-        #     "uid": self.client_uid,
-        #     **data_dict
-        # }
         try:
             self.websocket.send(
                Message(result=data, request_id=self.client_uid).model_dump_json(by_alias=True)

     whisper_model = None
     llm_model = None
     vad_model = None
     @classmethod
     def initializer(cls, event:mp.Event, warmup=True):
         # init llamacpp
         cls.llm_model = QwenTranslator(config.LLM_MODEL_PATH, config.LLM_SYS_PROMPT)
         cls.vad_model = VoiceActivityDetector()
         event.set()
             )
     def send_to_client(self, data:TransResult):
         try:
             self.websocket.send(
                Message(result=data, request_id=self.client_uid).model_dump_json(by_alias=True)