sa-ma/tos-simplifier

ToS Simplifier

sa-ma/tos-simplifier is a fine-tuned Longformer Encoder–Decoder (LED) model that turns dense, jargon-filled Terms of Service (ToS) documents into clear, plain-English summaries. The underlying LED architecture processes sequences up to 16 384 tokens in one pass, making it ideal for very long contracts.:contentReference[oaicite:0]{index=0}

Model details

Base model	allenai/led-base-16384
Parameters	~162 M
Context window	16 384 tokens (encoder) / 1 024 (decoder)
Language	English
License	MIT

Training

The model was fine-tuned on an internal corpus of publicly available ToS and their human-written “plain language” summaries (≈ 1.2 k document–summary pairs).
Key hyper-parameters:

• Optimiser — Adam W (β₁ = 0.9, β₂ = 0.98)
• Learning-rate — 3 × 10⁻⁵ with linear warm-up
• Batch — 16 effective (8 × 2 GPUs, gradient-accumulation = 2)
• Early-stop on validation ROUGE-L

Full settings are stored in training_args.bin.

Intended use

✔ What it’s for	✖ What it’s not for
Summarising ToS, privacy policies, EULAs	Non-English input
General long-form abstractive summarisation	Producing legally binding advice
Making legal texts more accessible	Summarising sensitive or proprietary data without review

Quick start

from transformers import LEDTokenizer, LEDForConditionalGeneration, pipeline

model_id = "sa-ma/tos-simplifier"
summariser = pipeline(
    "summarization",
    model=model_id,
    tokenizer=model_id,
    device_map="auto",       # drop or change if running on CPU
    max_length=256,
    min_length=30,
)

long_doc = open("tos.txt").read()
summary = summariser(long_doc)[0]["summary_text"]
print(summary)