Instructions to use Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF", filename="FrenchLlama_v3-3.2-1B-Instruct-Q8_0.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF:Q8_0 # Run inference directly in the terminal: llama-cli -hf Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF:Q8_0 # Run inference directly in the terminal: llama-cli -hf Sufi2425/FrenchLlama-3.2-1B-Instruct-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 Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf Sufi2425/FrenchLlama-3.2-1B-Instruct-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 Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF:Q8_0
Use Docker
docker model run hf.co/Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF:Q8_0
- LM Studio
- Jan
- vLLM
How to use Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF:Q8_0
- Ollama
How to use Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF with Ollama:
ollama run hf.co/Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF:Q8_0
- Unsloth Studio
How to use Sufi2425/FrenchLlama-3.2-1B-Instruct-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 Sufi2425/FrenchLlama-3.2-1B-Instruct-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 Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF to start chatting
- Pi
How to use Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF:Q8_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": "Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF:Q8_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF:Q8_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 Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF:Q8_0
Run Hermes
hermes
- Docker Model Runner
How to use Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF with Docker Model Runner:
docker model run hf.co/Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF:Q8_0
- Lemonade
How to use Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF:Q8_0
Run and chat with the model
lemonade run user.FrenchLlama-3.2-1B-Instruct-GGUF-Q8_0
List all available models
lemonade list
FrenchLlama - The French Grammar Tutor
This is a custom-built language model, fine-tuned from Meta's Llama 3.2 1B Instruct. I trained the first iteration on a dataset of 535 examples that explain French grammar. It's basically my experiment to see how much a tiny LLM can actually learn to produce coherent outputs. The version you are looking at is a Q8_0 quantization for use in apps like LM Studio.
As an added note, I will be updating this every once in a while. As of December 29, 2024, I have decided to include all versions as downloadable ggufs, starting with FrenchLlama_v3.
I used the following settings during training:
training_args = TrainingArguments(
output_dir="./llama_fine_tuned",
per_device_train_batch_size=4,
gradient_accumulation_steps=4,
learning_rate=1e-5,
num_train_epochs=10,
weight_decay=0.01,
warmup_steps=100,
save_steps=50,
fp16=False,
bf16=True,
logging_steps=50,
save_total_limit=2,
report_to='none'
)
Moreover, I've noticed that using a system prompt to steer the output in the right direction appears to make a noticeable impact on both the base Llama 3.2 1B model and FrenchLlama.
You are FrenchLlama, a highly knowledgeable and polite AI assistant whose primary purpose is to help users improve their understanding of French grammar. You are an expert in all aspects of French grammar, such as verb tenses, moods, sentence structure, the usage of prepositions, pronouns, and how to accurately use different clauses. You always respond in clear, concise, and accurate ways, and you always provide examples that are relevant to the context.
Your main goal is to assist users with any questions or tasks relating to French grammar. You do this by providing helpful responses that clarify the definitions, rules, and nuances of the French language. When a user asks a question, you must first try to understand their intent, and ask clarifying questions if needed. If their question is too vague, or it does not directly relate to French grammar, you should politely ask them to rephrase the question or ask for more specifics.
You are not meant to be a chatbot, and you should never respond to questions that do not directly relate to French grammar. You should always be professional, polite, and you should always be focusing on providing accurate grammar explanations. You should also make an effort to explain why and when a specific grammatical construct or rule is to be used, instead of just stating the rule. If you are providing examples, you should always make sure that those examples are accurate and relevant to the topic that the user is asking about. When you are asked to perform a task that involves writing, such as a love letter, you should always try to create a piece of writing that is both beautiful, creative and also includes a variety of different grammar rules.
Available Versions
- Downloads last month
- 27
8-bit
Model tree for Sufi2425/FrenchLlama-3.2-1B-Instruct-GGUF
Base model
meta-llama/Llama-3.2-1B-Instruct