Instructions to use jpacifico/Vigalpaca-French-7B-ties-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use jpacifico/Vigalpaca-French-7B-ties-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="jpacifico/Vigalpaca-French-7B-ties-GGUF", filename="Vigalpaca-French-7B-ties-quantized-q8_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 jpacifico/Vigalpaca-French-7B-ties-GGUF 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 jpacifico/Vigalpaca-French-7B-ties-GGUF:Q8_0 # Run inference directly in the terminal: llama cli -hf jpacifico/Vigalpaca-French-7B-ties-GGUF:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf jpacifico/Vigalpaca-French-7B-ties-GGUF:Q8_0 # Run inference directly in the terminal: llama cli -hf jpacifico/Vigalpaca-French-7B-ties-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 jpacifico/Vigalpaca-French-7B-ties-GGUF:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf jpacifico/Vigalpaca-French-7B-ties-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 jpacifico/Vigalpaca-French-7B-ties-GGUF:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf jpacifico/Vigalpaca-French-7B-ties-GGUF:Q8_0
Use Docker
docker model run hf.co/jpacifico/Vigalpaca-French-7B-ties-GGUF:Q8_0
- LM Studio
- Jan
- Ollama
How to use jpacifico/Vigalpaca-French-7B-ties-GGUF with Ollama:
ollama run hf.co/jpacifico/Vigalpaca-French-7B-ties-GGUF:Q8_0
- Unsloth Studio
How to use jpacifico/Vigalpaca-French-7B-ties-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 jpacifico/Vigalpaca-French-7B-ties-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 jpacifico/Vigalpaca-French-7B-ties-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for jpacifico/Vigalpaca-French-7B-ties-GGUF to start chatting
- Atomic Chat new
- Docker Model Runner
How to use jpacifico/Vigalpaca-French-7B-ties-GGUF with Docker Model Runner:
docker model run hf.co/jpacifico/Vigalpaca-French-7B-ties-GGUF:Q8_0
- Lemonade
How to use jpacifico/Vigalpaca-French-7B-ties-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull jpacifico/Vigalpaca-French-7B-ties-GGUF:Q8_0
Run and chat with the model
lemonade run user.Vigalpaca-French-7B-ties-GGUF-Q8_0
List all available models
lemonade list
Vigalpaca-French-7B-ties-GGUF
Vigalpaca-French-7B-ties is a merge of the following models:
jpacifico/French-Alpaca-7B-Instruct-beta
bofenghuang/vigostral-7b-chat
base model : jpacifico/French-Alpaca-7B-Instruct-beta
Usage
This quantized q8_0 GGUF version can be used on a CPU device, compatible with llama.cpp Ollama and LM Studio.
Ollama Modelfile example :
FROM ./Vigalpaca-French-7B-ties-quantized-q8_0.gguf
TEMPLATE """[INST] {{ .System }} {{ .Prompt }} [/INST]"""
PARAMETER stop "[INST]"
PARAMETER stop "[/INST]"
SYSTEM """Tu es un assistant IA nommé Vigalpaca. Tu dois répondre de manière concise et bienveillante aux questions posées par l'utilisateur."""
Limitations
The Vigalpaca model is a quick demonstration that a base 7B model can be easily merged/fine-tuned to specialize in a particular language. It does not have any moderation mechanisms.
- Developed by: Jonathan Pacifico. Vigostral model by Bofeng Huang (special thanks), 2024
- Model type: LLM
- Language(s) (NLP): French
- License: Apache-2.0
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