Instructions to use 0sz1/IT-auditor-1.7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use 0sz1/IT-auditor-1.7B with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="0sz1/IT-auditor-1.7B",
	filename="SmolLM2-1.7B-Instruct.Q8_0.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use 0sz1/IT-auditor-1.7B with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf 0sz1/IT-auditor-1.7B:Q8_0
# Run inference directly in the terminal:
llama-cli -hf 0sz1/IT-auditor-1.7B:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf 0sz1/IT-auditor-1.7B:Q8_0
# Run inference directly in the terminal:
llama-cli -hf 0sz1/IT-auditor-1.7B: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 0sz1/IT-auditor-1.7B:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf 0sz1/IT-auditor-1.7B: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 0sz1/IT-auditor-1.7B:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf 0sz1/IT-auditor-1.7B:Q8_0

Use Docker

docker model run hf.co/0sz1/IT-auditor-1.7B:Q8_0

LM Studio
Jan
Ollama
How to use 0sz1/IT-auditor-1.7B with Ollama:
```
ollama run hf.co/0sz1/IT-auditor-1.7B:Q8_0
```

Unsloth Studio new

How to use 0sz1/IT-auditor-1.7B 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 0sz1/IT-auditor-1.7B 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 0sz1/IT-auditor-1.7B to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for 0sz1/IT-auditor-1.7B to start chatting

Docker Model Runner
How to use 0sz1/IT-auditor-1.7B with Docker Model Runner:
```
docker model run hf.co/0sz1/IT-auditor-1.7B:Q8_0
```

Lemonade

How to use 0sz1/IT-auditor-1.7B with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull 0sz1/IT-auditor-1.7B:Q8_0

Run and chat with the model

lemonade run user.IT-auditor-1.7B-Q8_0

List all available models

lemonade list

IT-auditor-1.7B-Alpha

IT-auditor-1.7B-Alpha is a specialized, privacy-first Small Language Model (SLM) designed to audit IT contracts and find "lethal" clauses for software developers and freelancers.

It is built on top of SmolLM2-1.7B-Instruct and fine-tuned on a high-density dataset of real-world tech agreements.

Key Features

Privacy-First: Designed to run 100% offline on consumer hardware (GTX 1650/3050). No data leaves your machine.
SEC EDGAR Grounding: Trained on verified filings from top tech companies (Apple, NVIDIA, Palantir).
Expert Distillation: Insights distilled from Llama-3-70B experts specifically for IT-law risk detection.
High Performance: Optimized for 4096 context window and blazing fast inference (60+ tokens/sec).

What it detects:

Uncapped Liability: Finds clauses where you risk your entire business.
Aggressive IP Transfers: Detects when you lose rights to your ideas before payment.
Unilateral Termination: Points out power imbalances in notice periods.
Payment Traps: Flags ambiguous "sole discretion" payment terms.

Benchmark (Alpha Preview)

In internal tests, IT-auditor detected 24-hour termination traps and "unpaid work" IP transfers that general-purpose 7B models often gloss over.

Usage (GGUF)

Recommended for use with LM Studio, Ollama, or llama.cpp.

System Prompt:

"You are a legal auditor. Your task is to find traps in contracts that hurt the developer and point them out clearly."

Research Background

This model is part of a broader study on Information Asymmetry and Semantic Entropy in recursive AI systems. For technical details, see my papers on Zenodo.

Contact & Custom Solutions

Need a custom model tuned on your proprietary corporate data? Looking for a 8B/70B high-precision version?

Email: serghei.zaghinaico@gmail.com
Papers: https://zenodo.org/records/19410403 ; https://zenodo.org/records/19431476

Disclaimer: This model is a research tool and does not constitute legal advice. Always consult with a human lawyer for final contract decisions.

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GGUF

Model size

2B params

Architecture

llama

Hardware compatibility

8-bit

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