Instructions to use Mathieu-Thomas-JOSSET/joke-finetome-model-gguf-phi4-20260110-090947 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Mathieu-Thomas-JOSSET/joke-finetome-model-gguf-phi4-20260110-090947 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 Mathieu-Thomas-JOSSET/joke-finetome-model-gguf-phi4-20260110-090947:Q4_K_M # Run inference directly in the terminal: llama cli -hf Mathieu-Thomas-JOSSET/joke-finetome-model-gguf-phi4-20260110-090947:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Mathieu-Thomas-JOSSET/joke-finetome-model-gguf-phi4-20260110-090947:Q4_K_M # Run inference directly in the terminal: llama cli -hf Mathieu-Thomas-JOSSET/joke-finetome-model-gguf-phi4-20260110-090947:Q4_K_M
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 Mathieu-Thomas-JOSSET/joke-finetome-model-gguf-phi4-20260110-090947:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Mathieu-Thomas-JOSSET/joke-finetome-model-gguf-phi4-20260110-090947:Q4_K_M
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 Mathieu-Thomas-JOSSET/joke-finetome-model-gguf-phi4-20260110-090947:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Mathieu-Thomas-JOSSET/joke-finetome-model-gguf-phi4-20260110-090947:Q4_K_M
Use Docker
docker model run hf.co/Mathieu-Thomas-JOSSET/joke-finetome-model-gguf-phi4-20260110-090947:Q4_K_M
- Llama new
- LM Studio
- Jan
- vLLM
How to use Mathieu-Thomas-JOSSET/joke-finetome-model-gguf-phi4-20260110-090947 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Mathieu-Thomas-JOSSET/joke-finetome-model-gguf-phi4-20260110-090947" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Mathieu-Thomas-JOSSET/joke-finetome-model-gguf-phi4-20260110-090947", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Mathieu-Thomas-JOSSET/joke-finetome-model-gguf-phi4-20260110-090947:Q4_K_M
- Ollama
How to use Mathieu-Thomas-JOSSET/joke-finetome-model-gguf-phi4-20260110-090947 with Ollama:
ollama run hf.co/Mathieu-Thomas-JOSSET/joke-finetome-model-gguf-phi4-20260110-090947:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use Mathieu-Thomas-JOSSET/joke-finetome-model-gguf-phi4-20260110-090947 with Docker Model Runner:
docker model run hf.co/Mathieu-Thomas-JOSSET/joke-finetome-model-gguf-phi4-20260110-090947:Q4_K_M
- Lemonade
How to use Mathieu-Thomas-JOSSET/joke-finetome-model-gguf-phi4-20260110-090947 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Mathieu-Thomas-JOSSET/joke-finetome-model-gguf-phi4-20260110-090947:Q4_K_M
Run and chat with the model
lemonade run user.joke-finetome-model-gguf-phi4-20260110-090947-Q4_K_M
List all available models
lemonade list
- Atomic Chat
joke-finetome-model-gguf-phi4-20260110-090947 : GGUF
This model was finetuned and converted to GGUF format using Unsloth.
Example usage:
- For text only LLMs:
./llama.cpp/llama-cli -hf Mathieu-Thomas-JOSSET/joke-finetome-model-gguf-phi4-20260110-090947 --jinja - For multimodal models:
./llama.cpp/llama-mtmd-cli -hf Mathieu-Thomas-JOSSET/joke-finetome-model-gguf-phi4-20260110-090947 --jinja
Available Model files:
phi-4.Q4_K_M.gguf
Ollama
An Ollama Modelfile is included for easy deployment.
This was trained 2x faster with Unsloth

Training artifacts
- Plot (interactive):
reports/training_loss_step.html - Run manifest:
reports/run_manifest.json - Inference sample:
reports/inference_sample.json - Config snapshot:
reports/config_snapshot.json
Inference
This repository contains a GGUF model intended to be used with llama.cpp and/or deployed on Hugging Face Inference Endpoints (llama.cpp container).
Recommended Inference Endpoints knobs:
- Max tokens / request: 1024
- Max concurrent requests: 2
Local llama.cpp (Phi-4 template)
llama-cli -hf Mathieu-Thomas-JOSSET/joke-finetome-model-gguf-phi4-20260110-090947:Q4_K_M -cnv --chat-template phi4
Hugging Face Inference Endpoint (llama.cpp)
When creating an endpoint, select this repo and the GGUF file .gguf (quant: Q4_K_M).
Recommended settings are stored in: inference/endpoint_recipe.json.
Python client example: inference/hf_endpoint_client.py
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