| --- |
| license: mit |
| language: |
| - en |
| metrics: |
| - bertscore |
| - rouge |
| base_model: |
| - allenai/led-base-16384 |
| --- |
| |
| # 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 |
|
|
| ```python |
| 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) |
| |
