NNiceVois
Photos to model · One-tap training

Teach AI your face, your product, or your style

Upload 8–40 photos, say what they show, and press Train. NiceVois builds an image model of your subject, generates new pictures with it right here, and hands you the trained model file — yours to download and keep.

  • Nothing to install — it all runs in the browser
  • One press to start; ready in about an hour
  • You keep the model file, and it works outside NiceVois
You own the model filePrivate to your accountWorks with standard tools

Your first model is free. One full-strength run on the house, at any image count and any training depth. Further runs are quoted before they start and draw on prepaid NiceVois balance, which is not currently sold — so the free run is the whole offer for a new account today.

Image model trainer

Build your model

Checking benchmark status…
What are the images teaching?

Recommended for your image count. More steps learn the subject more strongly and take longer.

Drop 8–40 images here

or choose images in any common format (JPG, PNG, WEBP, HEIC…), at least 512 × 512. Drop more at any time to add to the set.

0 of 8 minimum

Ten setup steps, reduced to three

Images in, portable model out

  1. 1
    Add 8–40 images

    Use varied, clear images you own or have permission to use — any common format works.

  2. 2
    Name the subject

    Choose person, product, character, or style. The training configuration stays out of your way.

  3. 3
    Train and keep the file

    Download the LoRA package and a short guide. You own the artifact, not an account-locked preset.

For the technically minded

Under the hood: a portable FLUX-compatible LoRA

  • What trains. A rank-16 LoRA on Flex.1-alpha (Apache-2.0), driven by ai-toolkit, at 250–2000 steps with a per-subject recommendation — a face is budgeted like an identity, not like a style.
  • What you download. The .safetensors adapter itself with its trigger word, the exact training manifest, and preview samples. Load it in ComfyUI, Forge, or any FLUX-compatible runtime — it is not locked to NiceVois.
  • What the pipeline does. Your images are captioned with the trigger word, normalized to upright PNG or JPEG, trained on an isolated cloud GPU, and the finished package is size- and SHA-256-verified before delivery.
  • Renders. On-page generation loads your adapter onto the same base model, and prompts are composed into the caption language the adapter was trained on.

What NiceVois is automating

Dataset validation, captions, dependency setup, model configuration, GPU execution, checkpoint selection, integrity checks, and output packaging.

What stays yours

Your source images remain private during the benchmark and expire after seven days. The finished LoRA is a file you can keep and use elsewhere.