Sign up free, get 10,000 credits

Starter credits added when you sign up.

Sign up and create 8 images for free

Starter credits added when you sign up.

LoRA Pengguna

XL
Peningkatan Perincian

Hyper SDXL

Hyper SDXL - AI Model cover image

Sign up free, get 10,000 credits

Starter credits added when you sign up.

Sign up and create 8 images for free

Starter credits added when you sign up.

Dimuat naik pada
15 Sep 2024, 4:28 PG
Kegunaan
33.4m
Ulasan
Cemerlang  (285)
Kebenaran
  • Allow image generation & sharing
  • Benarkan pengguna memuat turun model anda
  • Kegunaan komersial

Recommended LoRAs

Keterangan

https://huggingface.co/ByteDance/Hyper-SD/

tl;dr figure it out yourself scrub.

No longer downsized! Inferior to optimized checkpoint merges.

These are just suggestions. Experimentation is required and you will waste some credits to understand this LoRA. Weight: 0.8 - 1.0 Sampling method: Anything! Some models react very badly with certain samplers! I recommend either Euler, DDIM or Euler A.

The versions are NOT representative of number of steps you use! 2steps does NOT mean you should use only 2 steps! Sampling steps for 1step, 2steps: 4 minimum. Sampling steps for 4steps: 5 minimum. Sampling steps for 8steps: 8 minimum. Sampling steps for cod-4steps-CFG: 8 minimum.

Good sampling steps depends on the model that you use. A good number to start with is 7, then use higher steps or lower steps. CFG is usually around 1.0-1.8. It is completely dependent on which model that you use. A good number to start with is 1.5, then use higher or lower CFG

cod-4steps-CFG works with higher CFG, meaning you get to use CFG meaningfully as opposed to extremely low values. It still is dependant on the model. A good number to start with is 4.0, then use higher or lower CFG. For realistic models that often has lower CFG values, start with 2.0 instead.

TODO: rentry articles going in-depth about hyper-sd capabilities and shortcomings.

Cover artwork: https://pixai.art/artwork/1785851893719513342

Komen20

Karya oleh Hyper SDXL