Instructions to use MoYoYoTech/Translator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
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 new
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 new
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
| import unittest | |
| from unittest.mock import MagicMock, patch | |
| from transcribe.strategy import TranscriptStabilityAnalyzer, TranscriptChunk, TranscriptResult, SplitMode | |
| class TestTranscriptStabilityAnalyzer(unittest.TestCase): | |
| def setUp(self): | |
| self.analyzer = TranscriptStabilityAnalyzer() | |
| def test_first_chunk_yields_pending_text(self): | |
| mock_chunk = MagicMock(spec=TranscriptChunk) | |
| mock_chunk.join.return_value = "Hello world." | |
| with patch.object(self.analyzer._transcript_history, 'previous_chunk', return_value=None): | |
| results = list(self.analyzer.analysis(" ", mock_chunk, buffer_duration=5.0)) | |
| self.assertEqual(len(results), 1) | |
| self.assertIsInstance(results[0], TranscriptResult) | |
| self.assertIn("Hello", results[0].context) | |
| def test_short_buffer_with_high_similarity_and_end_sentence(self): | |
| curr_chunk = MagicMock(spec=TranscriptChunk) | |
| curr_first = MagicMock() | |
| curr_rest = [MagicMock()] | |
| prev_chunk = MagicMock(spec=TranscriptChunk) | |
| prev_first = MagicMock() | |
| # Mock the items attribute | |
| curr_chunk.items = [curr_first, curr_rest[0]] # Ensure it is iterable | |
| curr_chunk.get_split_first_rest.return_value = (curr_first, curr_rest) | |
| prev_chunk.get_split_first_rest.return_value = (prev_first, []) | |
| curr_first.compare.return_value = 0.85 | |
| curr_first.is_end_sentence.return_value = True | |
| curr_first.has_punctuation.return_value = True | |
| curr_first.join.return_value = "This is a test sentence." | |
| curr_first.get_buffer_index.return_value = 0 | |
| curr_rest[0].join.return_value = " Continuing..." | |
| with patch.object(self.analyzer._transcript_history, 'previous_chunk', return_value=prev_chunk): | |
| with patch.object(self.analyzer._transcript_history, 'add'): | |
| results = list(self.analyzer.analysis(" ", curr_chunk, buffer_duration=5.0)) | |
| self.assertGreaterEqual(len(results), 1) | |
| self.assertTrue(any(r.is_end_sentence for r in results)) | |
| self.assertTrue(any("test" in r.context for r in results)) | |
| def test_long_buffer_triggers_commit(self): | |
| chunk1 = MagicMock() | |
| chunk2 = MagicMock() | |
| chunk3 = MagicMock() | |
| chunk1.join.return_value = "Hello." | |
| chunk2.join.return_value = "How are" | |
| chunk3.join.return_value = " you?" | |
| mock_chunk = MagicMock(spec=TranscriptChunk) | |
| mock_chunk.split_by.return_value = [chunk1, chunk2, chunk3] | |
| mock_chunk.get_buffer_index.return_value = 0 | |
| with patch.object(self.analyzer._transcript_history, 'previous_chunk', return_value=MagicMock()): | |
| with patch.object(self.analyzer._transcript_history, 'add'): | |
| results = list(self.analyzer.analysis(" ", mock_chunk, buffer_duration=15.0)) | |
| self.assertTrue(any(r.is_end_sentence for r in results)) | |
| self.assertTrue(any("Hello" in r.context for r in results)) | |
| if __name__ == '__main__': | |
| unittest.main() | |