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 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
- 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-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
File size: 3,059 Bytes
aca8f40 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 | 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()
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