doohickey-mega huggingface.co api & doohickey doohickey-mega github AI Model

Introduction of doohickey-mega

Model Details of doohickey-mega

Models better suited for High-Resolution Image Synthesis. The main model (doohickey/doohickey-mega) has been finetuned from runwayml/stable-diffusion-v1-5 near a resolution of 768x768 (suggested method of generating from model is with Doohickey ).

Current models:

name	description	datasets used
doohickey/doohickey-mega/v1-3000steps.ckpt	first try, rlly good hd, bad results w/ other aspect ratios than 1:1 trained at 704x704	A-1k
doohickey/doohickey-mega/v2-3000steps.ckpt	same as last one but worse	A-1k + ~1k samples from LAION-2b-En-Aesthetic >=768x768
doohickey/doohickey-mega/v3-3000.ckpt	with new CLIP model ( laion/CLIP-ViT-L-14-laion2B-s32B-b82K ) (CLIP model also finetuned the 3k steps), models past this point were trained with various aspect ratios from 640x640 min to 768x768 max resolution. (examples 768x640 or 704x768)	A-1k + E-10k
doohickey/doohickey-mega/v3-6000.ckpt	3k steps on top of v3-3000.ckpt, better at hands! (just UNet finetune, added a RandomHorizontalFlip operation at 50%)	A-1k
doohickey/doohickey-mega/v3-7000.ckpt	continuation of last model, I thought Colab would crash after 3k steps but it kept going for a little while saving ckpts every 1k steps.	A-1k
doohickey/doohickey-mega/v3-8000.ckpt	see last description, v3-6000 + 2k steps	A-1k

The currently loaded model for diffusers is doohickey/doohickey-mega/v3-8000.ckpt

Datasets:

name	description
A-1K	1k scraped images, captioned with BLIP (more refined aesthetic)
E-10k	10k scraped images captioned with BLIP (less refined aesthetic)

Limitations and Biases from Stable Diffusion also apply to this model.

This model is open access and available to all, with a CreativeML OpenRAIL-M license further specifying rights and usage. The CreativeML OpenRAIL License specifies:

You can't use the model to deliberately produce nor share illegal or harmful outputs or content
The authors claim no rights on the outputs you generate, you are free to use them and are accountable for their use which must not go against the provisions set in the license
You may re-distribute the weights and use the model commercially and/or as a service. If you do, please be aware you have to include the same use restrictions as the ones in the license and share a copy of the CreativeML OpenRAIL-M to all your users (please read the license entirely and carefully) Please read the full license carefully here: https://huggingface.co/spaces/CompVis/stable-diffusion-license

Runs of doohickey doohickey-mega on huggingface.co

Total runs

24-hour runs

3-day runs

7-day runs

-16

30-day runs

More Information About doohickey-mega huggingface.co Model

doohickey-mega huggingface.co

doohickey-mega huggingface.co is an AI model on huggingface.co that provides doohickey-mega's model effect (), which can be used instantly with this doohickey doohickey-mega model. huggingface.co supports a free trial of the doohickey-mega model, and also provides paid use of the doohickey-mega. Support call doohickey-mega model through api, including Node.js, Python, http.

doohickey-mega huggingface.co Url

https://huggingface.co/doohickey/doohickey-mega

doohickey doohickey-mega online free

doohickey-mega huggingface.co is an online trial and call api platform, which integrates doohickey-mega's modeling effects, including api services, and provides a free online trial of doohickey-mega, you can try doohickey-mega online for free by clicking the link below.

doohickey doohickey-mega online free url in huggingface.co:

https://huggingface.co/doohickey/doohickey-mega

doohickey-mega install

doohickey-mega is an open source model from GitHub that offers a free installation service, and any user can find doohickey-mega on GitHub to install. At the same time, huggingface.co provides the effect of doohickey-mega install, users can directly use doohickey-mega installed effect in huggingface.co for debugging and trial. It also supports api for free installation.