FeiArt Handpainted CG Diffusion
is a custom diffusion model trained by @FeiArt_AiArt.

It can be used to create Handpainted CG style images.

To use it，you can use [FeiArt_Handpainted CG Diffusion](https://colab.research.google.com/drive/1u9ompOlBZMgIZc_KZvxIa3V6UD4Ch3dT?usp=sharing)

If you create a fun image with this model, please show your result and [@FeiArt_AiArt](https://twitter.com/FeiArt_AiArt)

Or you can join the [FeiArt Diffusion Discord](https://discord.gg/MkAsEpNnqs)
Share your work created with this model.
Exchange experiences and parameters.
And see more custom diffusion models


model_config.update({
          'attention_resolutions': '32,16,8',
          'class_cond': False,
          'diffusion_steps': 1000,
          'rescale_timesteps': True,
          'timestep_respacing': 'ddim100',
          'image_size': 512,
          'learn_sigma': True,
          'noise_schedule': 'linear',
          'num_channels': 256,
          'num_head_channels': 64,
          'num_res_blocks': 2,
          'resblock_updown': True,
          'use_checkpoint': use_checkpoint,
          'use_fp16': True,
          'use_scale_shift_norm': True,
          
          and change the model.load to below
          model.load_state_dict(torch.load(custom_path, map_location='cpu'), strict=False)
{"license": "cc"}
license:cc region:us
TAGS
#license-cc #region-us 

FeiArt Handpainted CG Diffusion
is a custom diffusion model trained by @FeiArt_AiArt.

It can be used to create Handpainted CG style images.

To use it，you can use FeiArt_Handpainted CG Diffusion

If you create a fun image with this model, please show your result and @FeiArt_AiArt

Or you can join the FeiArt Diffusion Discord
Share your work created with this model.
Exchange experiences and parameters.
And see more custom diffusion models


model_config.update({
          'attention_resolutions': '32,16,8',
          'class_cond': False,
          'diffusion_steps': 1000,
          'rescale_timesteps': True,
          'timestep_respacing': 'ddim100',
          'image_size': 512,
          'learn_sigma': True,
          'noise_schedule': 'linear',
          'num_channels': 256,
          'num_head_channels': 64,
          'num_res_blocks': 2,
          'resblock_updown': True,
          'use_checkpoint': use_checkpoint,
          'use_fp16': True,
          'use_scale_shift_norm': True,
          
          and change the URL to below
          model.load_state_dict(URL(custom_path, map_location='cpu'), strict=False)
TAGS
#license-cc #region-us 

passage: TAGS
#license-cc #region-us 
