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
- llama.cpp
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
- Pi
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
Commit ·
f49e9c9
1
Parent(s): 93d2288
add export data for test
Browse files
transcribe/whisper_llm_serve.py
CHANGED
|
@@ -58,7 +58,7 @@ class WhisperTranscriptionService(ServeClientBase):
|
|
| 58 |
self._transcrible_time_cost = 0.
|
| 59 |
self._translate_time_cost = 0.
|
| 60 |
if config.TEST:
|
| 61 |
-
self.
|
| 62 |
self._test_queue = queue.Queue()
|
| 63 |
self._test_thread = self._start_thread(self.test_data_loop)
|
| 64 |
|
|
@@ -66,7 +66,7 @@ class WhisperTranscriptionService(ServeClientBase):
|
|
| 66 |
|
| 67 |
def test_data_loop(self):
|
| 68 |
writer = TestDataWriter()
|
| 69 |
-
while not self.
|
| 70 |
test_data = self._test_queue.get()
|
| 71 |
writer.write(test_data) # Save test_data to CSV
|
| 72 |
|
|
@@ -307,4 +307,6 @@ class WhisperTranscriptionService(ServeClientBase):
|
|
| 307 |
"""停止所有处理线程并清理资源"""
|
| 308 |
self._translate_thread_stop.set()
|
| 309 |
self._frame_processing_thread_stop.set()
|
|
|
|
|
|
|
| 310 |
logger.info(f"Stopping transcription service for client: {self.client_uid}")
|
|
|
|
| 58 |
self._transcrible_time_cost = 0.
|
| 59 |
self._translate_time_cost = 0.
|
| 60 |
if config.TEST:
|
| 61 |
+
self._test_task_stop = threading.Event()
|
| 62 |
self._test_queue = queue.Queue()
|
| 63 |
self._test_thread = self._start_thread(self.test_data_loop)
|
| 64 |
|
|
|
|
| 66 |
|
| 67 |
def test_data_loop(self):
|
| 68 |
writer = TestDataWriter()
|
| 69 |
+
while not self._test_task_stop.is_set():
|
| 70 |
test_data = self._test_queue.get()
|
| 71 |
writer.write(test_data) # Save test_data to CSV
|
| 72 |
|
|
|
|
| 307 |
"""停止所有处理线程并清理资源"""
|
| 308 |
self._translate_thread_stop.set()
|
| 309 |
self._frame_processing_thread_stop.set()
|
| 310 |
+
if config.TEST:
|
| 311 |
+
self._test_task_stop.set()
|
| 312 |
logger.info(f"Stopping transcription service for client: {self.client_uid}")
|