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 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
- 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 @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
- OpenClaw new
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"
- 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
daihui.zhang commited on
Commit ·
62d476f
1
Parent(s): 471affe
fix init language setting bug
Browse files
transcribe/pipelines/pipe_whisper.py
CHANGED
|
@@ -30,4 +30,4 @@ class WhisperPipe(BasePipe):
|
|
| 30 |
for char in bytearray_chars.decode('utf-8', errors='replace'):
|
| 31 |
if unicodedata.category(char) != 'Cc': # 不可打印字符的分类为 'Cc'
|
| 32 |
printable.append(char)
|
| 33 |
-
return ''.join(printable)
|
|
|
|
| 30 |
for char in bytearray_chars.decode('utf-8', errors='replace'):
|
| 31 |
if unicodedata.category(char) != 'Cc': # 不可打印字符的分类为 'Cc'
|
| 32 |
printable.append(char)
|
| 33 |
+
return ''.join(printable).strip()
|
transcribe/whisper_llm_serve.py
CHANGED
|
@@ -40,7 +40,7 @@ class PyWhiperCppServe(ServeClientBase):
|
|
| 40 |
self.run_in_thread(self.speech_to_text)
|
| 41 |
self.run_in_thread(self.get_frame_from_queue)
|
| 42 |
|
| 43 |
-
self.text_sep = ""
|
| 44 |
|
| 45 |
def run_in_thread(self, func):
|
| 46 |
t = threading.Thread(target=func)
|
|
@@ -57,6 +57,7 @@ class PyWhiperCppServe(ServeClientBase):
|
|
| 57 |
def set_lang(self, src_lang, dst_lang):
|
| 58 |
self.language = src_lang
|
| 59 |
self.dst_lang = dst_lang
|
|
|
|
| 60 |
|
| 61 |
def add_frames(self, frame_np):
|
| 62 |
self._frame_queue.put(frame_np)
|
|
|
|
| 40 |
self.run_in_thread(self.speech_to_text)
|
| 41 |
self.run_in_thread(self.get_frame_from_queue)
|
| 42 |
|
| 43 |
+
self.text_sep = ""
|
| 44 |
|
| 45 |
def run_in_thread(self, func):
|
| 46 |
t = threading.Thread(target=func)
|
|
|
|
| 57 |
def set_lang(self, src_lang, dst_lang):
|
| 58 |
self.language = src_lang
|
| 59 |
self.dst_lang = dst_lang
|
| 60 |
+
self.text_sep = "" if self.language == "zh" else " "
|
| 61 |
|
| 62 |
def add_frames(self, frame_np):
|
| 63 |
self._frame_queue.put(frame_np)
|