README.md

metadata

tags:
  - gguf
  - llama.cpp
  - unsloth
license: mit
datasets:
  - Yusiko/lia_dataset
language:
  - az
  - en
base_model:
  - meta-llama/Llama-3.1-8B

🤓LIA (Llama 3.1 8B — Finetuned with Unsloth)

A finetuned Llama 3.1 8B model specialized for Local Intelligent Agent (LIA) intent parsing and local file/system actions. The model converts user requests into compact JSON that LIA executes safely.

For download LIA and more detailed information, refer to the link below.

• https://github.com/Yusiko99/LIA

Overview🧐

• Base: Llama 3.1 8B Instruct
• Method: Unsloth SFT (LoRA), merged for deployment
• Dataset: Custom, user-created (intent pairs)
• Output: Raw JSON only (no markdown), with keys: command_type, parameters, reasoning
• Primary goal: Deterministic intent parsing for desktop automation

😎Purpose and Tasks

• Parse file/folder operations: open, list, create, write, read, delete, copy, move, rename
• Interpret patterns (e.g., *.pdf) and paths
• Safe fallback to chat intent when not a file operation
• Produce stable JSON without code fences or extra prose

Example output:

{
  "command_type": "list_files",
  "parameters": {"path": "Downloads", "pattern": "*.pdf"},
  "reasoning": "User wants to list PDFs in Downloads"
}

😲Differences vs Original Llama 3.1 8B

• More consistent JSON-only answers for intent parsing
• Lower hallucination rate on file/command names
• Better handling of short/telegraphic commands
• Tuned for low temperature decoding (0.1–0.3)

Training (Unsloth)

• LoRA-based SFT on user dataset (input → JSON output pairs)
• Chat template aligned with Llama 3.1
• System prompt stresses: “Return raw JSON only”
• Adapters merged to a full checkpoint for serving

Quick start (Ollama):

ollama run hf.co/Yusiko/LIA:Q4_K_M

📃License and Credits

• Base: Meta Llama 3.1 8B Instruct (respect base license)
• Finetuning: Unsloth
• Packaging: Ollama
• LIA is protecting with MIT license

For questions or integration help, open an issue on the repository.