Realistic Vision

I am excited to present my latest Realistic checkpoint model based on SD3M. This model has undergone over 100k+ training steps, ensuring high-quality output.

About This Model:

This is a Photo Realistic model, capable of generating photorealistic images. No trigger words are needed. The model is designed to produce high-detail, high-resolution images that closely mimic real-life photographs.

Configuration Used for Training:

GPU: A6000x2
Dataset: A mix of 5k stock photos and my own dataset
Batch Size: 8
Optimizer: AdamW
Scheduler: Cosine with restarts
Learning Rate (LR): 1e-05
Epoch: Target of 300 epochs
Captioning: WD14 and BLIP mix

Quick Guide and Parameters:

Clip Encoder: Not required
VAE: Not required
Sampler: dpmpp_2m
Scheduler: sgm_uniform
Sampling Steps: 25+
CFG Scale: 3+

For better results, try using ComfyUI. Here is a workflow that is low-cost and efficient. Currently, upscaling is not possible due to specific reasons. I have reported the issue to the TA team, and hopefully, it will be fixed soon.

Realistic Vision

Aspect Ratios for Demo:

1:1 [1024x1024 square]
8:5 [1216x768 landscape]
4:3 [1152x896 landscape]
3:2 [1216x832 landscape]
7:5 [1176x840 landscape]
16:9 [1344x768 landscape]
21:9 [1536x640 landscape]
19:9 [1472x704 landscape]
3:4 [896x1152 portrait]
2:3 [832x1216 portrait]
5:7 [840x1176 portrait]
9:16 [768x1344 portrait]
9:21 [640x1536 portrait]
5:8 [768x1216 portrait]
9:19 [704x1472 portrait]

Important: Do not include NSFW-related/mature words or censor words in your prompt. Doing so may result in unreliable or undesirable image outcomes.

Note:

This is not a merged or modified model. It is the original Realistic Vision fine-tuned model. Some users have been spreading incorrect information in the model's comment section. If you have any questions or want to know more, join my Discord server or share your thoughts in the comment section. Thank you for your time.