Humanize Llama text and give it a voice of its own
Llama is the model people run themselves: on a laptop, on a rented server, inside a product they built. That means the text arriving at Humanize 360 from Llama comes from a hundred different setups with a hundred different prompts. What they share is the habit people notice most: the writing is plain and generic, correct in every sentence and specific in none. It could be about anything.
The other habits: repetition of the same phrase or structure two or three times in a passage, as if the model lost track of what it had already said; a small working vocabulary, so "important", "help" and "ensure" do a lot of lifting; sentence openers that repeat ("This means that", "It is also"); and an even, mild register with no opinion in it.
The engine gives generic text variety, but it cannot give it your specifics. So this page pairs the humanizer with a custom style profile: paste 300 words of your own writing and the engine rewrites toward your contraction rate, sentence length and vocabulary spread. Try the box above first. Free for 300 words.
What flags a Llama draft on the detector
Vocabulary spread is the leading signal: few distinct words for the length of the text. Opener repetition is second, because the same sentence starters recur. Structural sameness and paragraph uniformity follow, since each paragraph is built from the same three moves. Word predictability is high because plain, common words in plain, common orders are what a language model predicts best. Stock-phrase density varies with the prompt; a well-instructed Llama can be clean on that signal and still read as generic.
What the engine does with it
- Widens the vocabulary toward words at the same level of formality, not fancier ones.
- Removes repeated phrases and rewrites repeated sentence shapes.
- Varies openers so consecutive sentences do not start the same way.
- Changes paragraph length so the page stops looking like a grid.
- With a style profile loaded, matches your own measured contraction rate and sentence rhythm instead of a generic target.
Mode and strength
Standard at Heavy is the usual choice for Llama text, because the tells are spread through every sentence rather than concentrated in a few phrases. If you run Llama inside your own product and need to humanize output at volume, the Pro plan includes API access and the same engine. A developer in Bangalore cleaning support replies and a writer in Lagos using a local Llama for first drafts both benefit more from a style profile than from any single mode.
Check it, then add the specifics
Run the draft through the free detector and note vocabulary spread and opener repetition. Humanize, run again, and read it. Then ask a question the engine cannot answer: what in this text could only have been written by someone who knows the subject? If the answer is nothing, add a number, a name, a place or a mistake you once made. Generic text becomes yours through detail, and no engine supplies detail.
Common questions
I fine-tuned Llama on my own writing. Do I still need this?
Possibly not. Run the output through the free detector first. If vocabulary spread and opener repetition are green, leave it alone. The humanizer is for text that carries the tells, not for text that does not.
Can I use Humanize 360 through an API for Llama output?
Yes. The Pro plan includes API access with the same modes, strengths and protected words as the web app. Enterprise wholesale words are available from 50,000 words for higher volumes.
Does the engine make the text longer to add variety?
No. Standard mode keeps length roughly the same. If the draft is thin, Expand mode adds development to points already present; it does not invent facts, which is why you should add specifics yourself.
Is my text sent to Meta or any other company?
No. The engine is ours. Text is processed on our own servers and, for anonymous runs, discarded as soon as the result is returned.