Generalis V1

Attempt at merging several models v1.5 into one general purpose model.

Focus has been put into simple prompts, good one-off generation, muted colours, low memory usage, small model size.

It is intended as easy model for use in larger projects where image generation is needed.

Published under CC0

Use example:

import torch    # Tested with 2.0.1+cu118
from diffusers import StableDiffusionPipeline    # <3


# Model location in HF 
model = "https://huggingface.co/vluz/Generalis_V1/blob/main/Generalis_v1.safetensors"

# Create pipe
pipe = StableDiffusionPipeline.from_ckpt(model, 
    torch_dtype=torch.float16, 
    safety_checker=None,
    feature_extractor=None,
    requires_safety_checker=False,)

# Cleanup
del pipe.vae.encoder
torch.cuda.empty_cache()

# Send to GPU
pipe = pipe.to("cuda")

# Optimize for low vram use and clear cache again
pipe.enable_vae_tiling()
pipe.enable_attention_slicing("max")
pipe.enable_xformers_memory_efficient_attention(attention_op=None)
pipe.unet.to(memory_format=torch.channels_last)
pipe.enable_sequential_cpu_offload()
torch.cuda.empty_cache()

# Set a prompt
prompt = "a cat"

# Generate image based on prompt
image = pipe(prompt).images[0]

# Save result image to disk
image.save("cat.png")