Instructions to use jpacifico/French-Alpaca-Phi-3-beta-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use jpacifico/French-Alpaca-Phi-3-beta-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("jpacifico/French-Alpaca-Phi-3-beta-GGUF", dtype="auto")

llama-cpp-python

How to use jpacifico/French-Alpaca-Phi-3-beta-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="jpacifico/French-Alpaca-Phi-3-beta-GGUF",
	filename="French-Alpaca-Phi-3-Mini-4k-Instruct-quantized-q8_0-v1.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/French-Alpaca-Phi-3-beta-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/French-Alpaca-Phi-3-beta-GGUF:Q8_0
# Run inference directly in the terminal:
llama cli -hf jpacifico/French-Alpaca-Phi-3-beta-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/French-Alpaca-Phi-3-beta-GGUF:Q8_0
# Run inference directly in the terminal:
llama cli -hf jpacifico/French-Alpaca-Phi-3-beta-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/French-Alpaca-Phi-3-beta-GGUF:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf jpacifico/French-Alpaca-Phi-3-beta-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/French-Alpaca-Phi-3-beta-GGUF:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf jpacifico/French-Alpaca-Phi-3-beta-GGUF:Q8_0

Use Docker

docker model run hf.co/jpacifico/French-Alpaca-Phi-3-beta-GGUF:Q8_0

LM Studio
Jan
Ollama
How to use jpacifico/French-Alpaca-Phi-3-beta-GGUF with Ollama:
```
ollama run hf.co/jpacifico/French-Alpaca-Phi-3-beta-GGUF:Q8_0
```

Unsloth Studio

How to use jpacifico/French-Alpaca-Phi-3-beta-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/French-Alpaca-Phi-3-beta-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/French-Alpaca-Phi-3-beta-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/French-Alpaca-Phi-3-beta-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use jpacifico/French-Alpaca-Phi-3-beta-GGUF with Docker Model Runner:
```
docker model run hf.co/jpacifico/French-Alpaca-Phi-3-beta-GGUF:Q8_0
```

Lemonade

How to use jpacifico/French-Alpaca-Phi-3-beta-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull jpacifico/French-Alpaca-Phi-3-beta-GGUF:Q8_0

Run and chat with the model

lemonade run user.French-Alpaca-Phi-3-beta-GGUF-Q8_0

List all available models

lemonade list

French-Alpaca-Phi-3-GGUF

French-Alpaca is a 3B params LLM model based on microsoft/Phi-3-mini-4k-instruct ,
fine-tuned from the original French-Alpaca-dataset entirely generated with OpenAI GPT-3.5-turbo.
The fine-tuning method is inspired from https://crfm.stanford.edu/2023/03/13/alpaca.html

This quantized f16 GGUF version can be used on a CPU device, compatible llama.cpp
Unsupported architecture by LM Studio.

Limitations

The French-Alpaca models family is a quick demonstration that a small LM ( < 8B params )
can be easily fine-tuned to specialize in a particular language. It does not have any moderation mechanisms.

Developed by: Jonathan Pacifico, 2024
Model type: LLM
Language(s) (NLP): French
License: MIT
Finetuned from model : microsoft/Phi-3-mini-4k-instruct

Downloads last month: 10

GGUF

Model size

4B params

Architecture

phi3

Hardware compatibility

8-bit

Inference Providers NEW

This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

jpacifico
/

French-Alpaca-Phi-3-beta-GGUF

French-Alpaca-Phi-3-GGUF

Limitations

Dataset used to train jpacifico/French-Alpaca-Phi-3-beta-GGUF

Collection including jpacifico/French-Alpaca-Phi-3-beta-GGUF

French-Alpaca 🦙