FOR TRAINING AND RESEARCH PURPOSES ONLY. Not for operational policing, legal advice, or use as evidence in any proceedings. The creator accepts no responsibility or liability for any use or misuse of this model. Model outputs may be inaccurate or incomplete.
Model Description
This is the Q8_0 GGUF quantised version of EryriLabs/PIT, reduced from ~39 GB (F16) to 21 GB with near-lossless quality. All weights are quantised to 8-bit integers, offering an excellent balance between quality preservation and reduced memory footprint.
PIT (Police Interview Trainer) is a domain-adapted language model for UK police interview roleplay training. It simulates realistic suspect behaviour across multiple scenario types, enabling trainee officers to practise the PEACE interview framework in a safe environment.
Base model:unsloth/gpt-oss-20b — a 21B parameter Mixture-of-Experts model with 3.6B active parameters per forward pass.
Training Pipeline
The model was created through a three-stage training pipeline, with all adapters merged before GGUF conversion:
1. Continued Pre-Training (CPT) — UK Criminal Law
Corpus: ~10.7 million tokens of UK criminal law material
Coverage: Legislation, case law, PACE codes, CPS guidance, sentencing guidelines
Adapter: LoRA r=64, 3 epochs, 1,971 steps
2. Continued Pre-Training (CPT) — Police Interview Technique
Corpus: ~53,000 tokens of PIP Level 1 interview training material
All three adapter layers were reconstructed on the base model, merged, and converted to GGUF format with Q8_0 quantisation. This applies 8-bit integer quantisation across all weights, providing near-lossless quality compared to the full-precision model.
Direct Q&A about PEACE framework and interview law
Witness roleplay
60
In-character witness responses
Scenario presentation
33
Generating interview briefing scenarios
Special procedures
30
Handling vulnerable suspects, appropriate adults, mental health
Available Quantisations
Quantisation
Size
Format
Notes
Q8_0 (this model)
21 GB
GGUF
Near-lossless 8-bit quantisation
Quick Start
Using with llama.cpp
bash
1# Download the model2huggingface-cli download EryriLabs/PIT-Q8_0 pit_q8_0.gguf --local-dir .34# Run with llama-server5llama-server -m pit_q8_0.gguf -c 8192 -ngl 99
Then open http://localhost:8080 for the built-in chat UI.
Using with Ollama
bash
1# Create a Modelfile2cat<<EOF> Modelfile3FROM ./pit_q8_0.gguf
4PARAMETER temperature 0.7
5PARAMETER num_ctx 8192
6SYSTEM "You are PIT (Police Interview Trainer), simulating a suspect in a police interview training exercise."
7EOF89# Create and run10ollama create pit -f Modelfile
11ollama run pit
Using with LM Studio
Download pit_q8_0.gguf
Place in your LM Studio models directory
Load the model and begin chatting
Using the full PIT application (recommended)
The PIT application includes a web interface with scenario selection, interview simulation, transcript recording, and automated assessment.
bash
1cd pit-app
2docker compose up
Then open http://localhost:3000.
Requirements:
GPU with 24GB+ VRAM (single GPU) or 2x 12GB+ GPUs with layer splitting
~21 GB disk space
Example prompt
<|system|>
You are PIT (Police Interview Trainer), simulating a suspect in a police interview training exercise.
YOUR CHARACTER: Tyler Bennett, 23 years old, male.
BEHAVIOUR: cooperative
INSTRUCTIONS:
- Stay in character throughout
- Use natural everyday speech
- Keep responses to 1-3 sentences
<|end|>
<|user|>
I am cautioning you. You do not have to say anything. But it may harm your defence if you do not mention when questioned something which you later rely on in court. Anything you do say may be given in evidence. Do you understand the caution?
<|end|>
<|assistant|>
Intended Use
Police interview training and education
Academic research into interview techniques
Roleplay simulation for PEACE framework practice
PIP Level 1 assessment preparation
Out of Scope
Operational policing decisions
Legal advice or guidance
Evidence in any legal proceedings
Replacement for human interview training supervision
Any commercial use without explicit permission
Technical Details
Architecture: Mixture-of-Experts (MoE), 21B total / 3.6B active parameters
THIS MODEL IS PROVIDED FOR TRAINING AND RESEARCH PURPOSES ONLY.
This model is not intended for, and should not be used in, operational policing, legal proceedings, or any context where its outputs could affect real individuals or cases. The model may generate inaccurate, incomplete, or inappropriate content. The creator accepts no responsibility or liability whatsoever for any use or misuse of this model or its outputs.
Users are solely responsible for ensuring their use complies with all applicable laws and regulations.
Training data might contain public sector information licensed under the Open Government Licence v3.0 and information licensed under the Non-Commercial College Licence.
