How Greenwashing Language Detector works
Press Load model once: your browser downloads Gemma 4 E2B instruction-tuned (web build) (2.0 GB) from this site and keeps it in its cache. Then add your text and press Classify locally. The model runs on this device using your graphics card, so nothing you enter is sent to a server. Until the model is loaded, or if your device cannot run it, the tool falls back to a simple keyword check and labels the result as the fallback.
Gemma 4 E2B instruction-tuned (web build) is a small open language model from Google. The tool sends it the instruction below plus your text, asks for a JSON answer with fixed fields, and shows each field as a card. It runs at temperature 0, so the same input gives the same answer on the same device, though different graphics cards can word it slightly differently.
Inputs longer than 6,000 characters are cut to that length before they reach the model, and the result says so. The model only sees what you paste: it does not look anything up.
The instruction the model gets
You review marketing copy for greenwashing language. Flag environmental words or phrases that are vague, absolute or unsupported (eco-friendly, green, natural, sustainable, planet-positive, carbon neutral, recyclable without detail), note any specific evidence the copy gives, and say what proof would make each claim checkable. Do not say whether the copy breaks any law and do not invent certifications.
What it returns
- Flagged wording: Each vague or unsupported phrase, quoted, with a short reason.
- Specific claims: Claims the copy backs with a figure, certification or scope, quoted.
- Proof that would help: For each flagged phrase, the evidence that would make it checkable.
- Plainer wording: A more specific version of the main claim, using only facts in the copy.