Fantasy Vision DiT

Fantasy Vision Model Overview

I’m excited to introduce my latest checkpoint model, based on HunyuanDiT-v1.2. This model has been trained over 60,000 steps to ensure the generation of high-quality fantasy-themed images with vibrant details images.

Model Details :

• Type: Photorealistic model/fantasy-themed/vibrant details

• Trigger Words: None required

• Chinese language support: No

• Output: High-detail, high-resolution images that closely resemble real-life photographs

Configuration Used for Training:

• GPU: A6000

• Dataset: Combination of 2 stock photos and my own custom dataset

• Batch Size: 1

• Optimizer: AdamW

• Scheduler: Cosine

• Learning Rate: 1e-5

• Epochs: Target of 100 epochs

• Captioning: GPT4

Quick Guide and Parameters:

• VAE: SDXL

• Sampler: dpmpp_2m

• Scheduler: sgm_uniform (Recommended for best results)

• Sampling Steps: 25+

• CFG Scale: 7

Available on tensor.art with Free GPU acceleration

• Tensor.art V1

• Tensor.art V2

For better results, try using ComfyUI

• workflow

Important: Please avoid using NSFW/mature content in your prompts, as it may lead to unreliable results. Additionally, shorter prompts tend to work better with both SD3 and DiT models.

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.