---
license: apache-2.0
library_name: transformers
tags:
  - t5
  - text2text-generation
  - security
  - arbiter
---

# Arbiter — T5 log Q&A

## What this is

A **T5** conditional-generation checkpoint fine-tuned for **[Arbiter](https://github.com/SentinelSage/arbiter)**.

Used for **log-oriented** prompts (e.g. explaining or answering questions about a security log string). The app generates a short text response via `T5ForConditionalGeneration.generate(...)`.

## Project

Part of **Arbiter** (Django + React): paste a security log or ask a cybersecurity question.

This repository holds **weights only**. Application code: [github.com/SentinelSage/arbiter](https://github.com/SentinelSage/arbiter).

## Training note

This is a **custom fine-tune**, not an unmodified public T5 base/small checkpoint. A generic Hub T5 model is not a guaranteed substitute for this artifact.

**Training data:** custom-curated, **unpublished** project data. Training tables are not published with the app.

## Intended use

- Running the Arbiter full-ML path locally
- Experimentation and educational use with the companion application

**Not** a production SOC product. No warranty. Generated text can be incomplete or incorrect; do not use for live security operations without your own validation.

## How Arbiter loads it

Local path after download:

```text
backend/models/cyber_qa_t5_model_log/
```

Loaded with `T5ForConditionalGeneration.from_pretrained(<local_or_hub_id>)` when `ARBITER_DEMO_MODE=false`.

## Files

Expect a standard Transformers export, e.g. `model.safetensors`, `config.json`, `spiece.model`, tokenizer config files.

## Method / citations

- **T5:** Raffel, C., et al. (2020). *Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer.* JMLR.  
  [T5 docs](https://huggingface.co/docs/transformers/model_doc/t5)
- **Transformers:** Wolf, T., et al. (2020). *Transformers: State-of-the-Art Natural Language Processing.* EMNLP.  
  [huggingface/transformers](https://github.com/huggingface/transformers)
- **PyTorch:** Paszke, A., et al. (2019). *PyTorch: An Imperative Style, High-Performance Deep Learning Library.* NeurIPS.  
  [pytorch/pytorch](https://github.com/pytorch/pytorch)

## Safety

Research / portfolio demo only. Do not paste production logs, PII, or credentials into shared demos using these weights.

## License

Apache License 2.0. Demo only — provided as-is, without warranty of any kind.

Copyright 2026 Ryan Vong / Sentinel Sage