Instructions to use pltobing/translategemma-4b-it-Q8_0-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pltobing/translategemma-4b-it-Q8_0-GGUF with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="pltobing/translategemma-4b-it-Q8_0-GGUF") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("pltobing/translategemma-4b-it-Q8_0-GGUF", dtype="auto") - llama-cpp-python
How to use pltobing/translategemma-4b-it-Q8_0-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="pltobing/translategemma-4b-it-Q8_0-GGUF", filename="translategemma-4b-it-q8_0.gguf", )
llm.create_chat_completion( messages = "\"Меня зовут Вольфганг и я живу в Берлине\"" )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use pltobing/translategemma-4b-it-Q8_0-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf pltobing/translategemma-4b-it-Q8_0-GGUF:Q8_0 # Run inference directly in the terminal: llama-cli -hf pltobing/translategemma-4b-it-Q8_0-GGUF:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf pltobing/translategemma-4b-it-Q8_0-GGUF:Q8_0 # Run inference directly in the terminal: llama-cli -hf pltobing/translategemma-4b-it-Q8_0-GGUF:Q8_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 pltobing/translategemma-4b-it-Q8_0-GGUF:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf pltobing/translategemma-4b-it-Q8_0-GGUF:Q8_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 pltobing/translategemma-4b-it-Q8_0-GGUF:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf pltobing/translategemma-4b-it-Q8_0-GGUF:Q8_0
Use Docker
docker model run hf.co/pltobing/translategemma-4b-it-Q8_0-GGUF:Q8_0
- LM Studio
- Jan
- Ollama
How to use pltobing/translategemma-4b-it-Q8_0-GGUF with Ollama:
ollama run hf.co/pltobing/translategemma-4b-it-Q8_0-GGUF:Q8_0
- Unsloth Studio new
How to use pltobing/translategemma-4b-it-Q8_0-GGUF 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 pltobing/translategemma-4b-it-Q8_0-GGUF 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 pltobing/translategemma-4b-it-Q8_0-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for pltobing/translategemma-4b-it-Q8_0-GGUF to start chatting
- Docker Model Runner
How to use pltobing/translategemma-4b-it-Q8_0-GGUF with Docker Model Runner:
docker model run hf.co/pltobing/translategemma-4b-it-Q8_0-GGUF:Q8_0
- Lemonade
How to use pltobing/translategemma-4b-it-Q8_0-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull pltobing/translategemma-4b-it-Q8_0-GGUF:Q8_0
Run and chat with the model
lemonade run user.translategemma-4b-it-Q8_0-GGUF-Q8_0
List all available models
lemonade list
Access Gemma on Hugging Face
This repository is publicly accessible, but you have to accept the conditions to access its files and content.
To access Gemma on Hugging Face, you’re required to review and agree to Google’s usage license. To do this, please ensure you’re logged in to Hugging Face and click below. Requests are processed immediately.
Log in or Sign Up to review the conditions and access this model content.
TranslateGemma GGUF Q8_0
Device: CPU/GPU
Language: 55 languages (see model origin details)
Speed: ~10 token/s on m8a.xlarge (5th Gen AMD EPYC 9R45 CPU)
Model origin (see for model details): https://huggingface.co/google/translategemma-4b-it
By: Patrick Lumbantobing
Copyright@VertoX-AI
- Downloads last month
- 16
8-bit
Model tree for pltobing/translategemma-4b-it-Q8_0-GGUF
Base model
google/translategemma-4b-it