stabilityai

/

stable-diffusion-3-medium-diffusers

like 256

I understand I may be jumping the gun a little bit but if I run the example script

import torch
from diffusers import StableDiffusion3Pipeline

pipe = StableDiffusion3Pipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", torch_dtype=torch.float16)
pipe.to("cuda")

image = pipe(
    prompt="a photo of a cat holding a sign that says hello world",
    negative_prompt="",
    num_inference_steps=28,
    height=1024,
    width=1024,
    guidance_scale=7.0,
).images[0]

image.save("sd3_hello_world.png")

I get a stack of errors, seems to be conflicts with the model.

A get loads of these style warnings, far to many to count...

/Volumes/SSD2TB/AI/Diffusers/lib/python3.10/site-packages/torch/nn/modules/module.py:2044: UserWarning: for pos_embed.proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)

and terminates with

    raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for SD3Transformer2DModel:
    Missing key(s) in state_dict: "pos_embed.pos_embed", "transformer_blocks.14.attn.to_add_out.weight", "transformer_blocks.14.attn.to_add_out.bias", "transformer_blocks.14.ff.net.0.proj.weight", "transformer_blocks.14.ff.net.0.proj.bias", "transformer_blocks.14.ff.net.2.weight", "transformer_blocks.14.ff.net.2.bias", "transformer_blocks.14.ff_context.net.0.proj.

listed what looks like all the keys