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"

Xin Zhang commited on Apr 23, 2025

Commit

e6f9f7a

1 Parent(s): ef2e75f

[fix]: update parameter.

Browse files

Files changed (1) hide show

transcribe/pipelines/pipe_vad.py +5 -4

transcribe/pipelines/pipe_vad.py CHANGED Viewed

@@ -36,7 +36,7 @@ class VadPipe(BasePipe):
                 threshold=0.5,
                 sampling_rate=cls.sample_rate,
                 # speech_pad_ms=10
-                min_silence_duration_ms = 150,
                 # speech_pad_ms = 30,
                 max_speech_duration_s=20.0,
                 )
@@ -60,8 +60,9 @@ class VadPipe(BasePipe):
     def update_silence_ms(self):
         min_silence = self.adaptive_ctrl.get_adaptive_silence_ms()
-        logging.error(f"🫠 update_silence_ms :{min_silence} => current: {self.vac.min_silence_duration_ms} ")
-        self.vac.min_silence_duration_ms = min_silence
     def process(self, in_data: MetaItem) -> MetaItem:
         if self._offset == 0:
@@ -72,7 +73,7 @@ class VadPipe(BasePipe):
         speech_data  = self._process_speech_chunk(source_audio)
         if speech_data: # 表示有音频的变化点出现
-            self.update_silence_ms()
             rel_start_frame, rel_end_frame = speech_data
             if rel_start_frame is not None and rel_end_frame is None:
                 self._status = "START" # 语音开始

                 threshold=0.5,
                 sampling_rate=cls.sample_rate,
                 # speech_pad_ms=10
+                min_silence_duration_ms = 100,
                 # speech_pad_ms = 30,
                 max_speech_duration_s=20.0,
                 )
     def update_silence_ms(self):
         min_silence = self.adaptive_ctrl.get_adaptive_silence_ms()
+        min_silence_samples = self.sample_rate * min_silence / 1000
+        self.vac.min_silence_samples = min_silence_samples
+        logging.warning(f"🫠 update_silence_ms :{min_silence} => current: {self.vac.min_silence_samples} ")
     def process(self, in_data: MetaItem) -> MetaItem:
         if self._offset == 0:
         speech_data  = self._process_speech_chunk(source_audio)
         if speech_data: # 表示有音频的变化点出现
+            # self.update_silence_ms()
             rel_start_frame, rel_end_frame = speech_data
             if rel_start_frame is not None and rel_end_frame is None:
                 self._status = "START" # 语音开始