Instructions to use minkdank/LLAMA-JSON-data-extration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use minkdank/LLAMA-JSON-data-extration 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 minkdank/LLAMA-JSON-data-extration:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf minkdank/LLAMA-JSON-data-extration:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf minkdank/LLAMA-JSON-data-extration:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf minkdank/LLAMA-JSON-data-extration: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 minkdank/LLAMA-JSON-data-extration:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf minkdank/LLAMA-JSON-data-extration: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 minkdank/LLAMA-JSON-data-extration:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf minkdank/LLAMA-JSON-data-extration:Q4_K_M

Use Docker

docker model run hf.co/minkdank/LLAMA-JSON-data-extration:Q4_K_M

LM Studio
Jan
Ollama
How to use minkdank/LLAMA-JSON-data-extration with Ollama:
```
ollama run hf.co/minkdank/LLAMA-JSON-data-extration:Q4_K_M
```

Unsloth Studio

How to use minkdank/LLAMA-JSON-data-extration 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 minkdank/LLAMA-JSON-data-extration 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 minkdank/LLAMA-JSON-data-extration to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for minkdank/LLAMA-JSON-data-extration to start chatting

Atomic Chat new
Docker Model Runner
How to use minkdank/LLAMA-JSON-data-extration with Docker Model Runner:
```
docker model run hf.co/minkdank/LLAMA-JSON-data-extration:Q4_K_M
```

Lemonade

How to use minkdank/LLAMA-JSON-data-extration with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull minkdank/LLAMA-JSON-data-extration:Q4_K_M

Run and chat with the model

lemonade run user.LLAMA-JSON-data-extration-Q4_K_M

List all available models

lemonade list

LLAMA-JSON-data-extration

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---
tags:
- gguf
- llama.cpp
- unsloth

---

# LLAMA-JSON-data-extration - GGUF

This model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth).

**Example usage**:
- For text only LLMs:    **llama-cli** **--hf** repo_id/model_name **-p** "why is the sky blue?"
- For multimodal models: **llama-mtmd-cli** **-m** model_name.gguf **--mmproj** mmproj_file.gguf

## Available Model files:
- `Llama-3.2-3B.Q8_0.gguf`