Model reference · open weights

MosaicArt

Available as managed deployment Image Guizmus · community Text→image 1 variants 858 dl/mo

MosaicArt is an open-weight image model from Guizmus. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.

Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.

What it is

Released byGuizmus
TypeImage models
TaskText→image
Parameters (lead)866M
Runs withdiffusers
Released2022-12-01
Popularity858 downloads / month
LicenceOpen weights

About

What MosaicArt is

Details

This is a Dreamboothed Stable Diffusion model trained on pictures of mosaic art.

The total dataset is made of 46 pictures. V2 was trained on Stable diffusion 2.1 768. I used StableTuner to do the training, using full caption on the pictures with almost no recurring word outside the main concept, so that no additionnal regularisation was needed. 6 epochs of 40 repeats on LR 1e-6 were used, with prior preservation.

Read the full model card

V1 was trained on runawayml 1.5 and the new VAE. I used EveryDream to do the training, using full caption on the pictures with almost no recurring word outside the main concept, so that no additionnal regularisation was needed. Out of e0 to e11 epochs, e8 was selected as the best application of style while not overtraining. Prior preservation was constated as good. A total of 9 epochs of 40 repeats with a learning rate of 1e-6.

The token "Mosaic Art" will bring in the new concept, trained as a style.

The recommended sampling is k_Euler_a or DPM++ 2M Karras on 20 steps, CFGS 7.5 .

Model v2

CKPT v2

YAML v2

Model v1

CKPT v1

CKPT v1 with ema weights

Dataset

🧨 Diffusers

This model can be used just like any other Stable Diffusion model. For more information, please have a look at the Stable Diffusion.

You can also export the model to ONNX, MPS and/or FLAX/JAX.

from diffusers import StableDiffusionPipeline
import torch

model_id = "Guizmus/MosaicArt"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "Mosaic Art dog on the moon"
image = pipe(prompt).images[0]

image.save("./MosaicArt.png")

From the published model card. Full card on the HuggingFace links in the sidebar.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys mosaicart for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (mosaicart below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/images/generations \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"mosaicart","prompt":"a red bicycle","size":"1024x1024"}'

Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.

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