Trying to run this on an M1 Mac Mini

by ryaker - opened

Changed CUDA to MPS, but getting errors.
You are using a model of type xlm-roberta to instantiate a model of type M-CLIP. This is not supported for all configurations of models and can yield errors.
loc("varianceEps"("(mpsFileLoc): /AppleInternal/Library/BuildRoots/c2cb9645-dafc-11ed-aa26-6ec1e3b3f7b3/Library/Caches/":228:0)): error: input types 'tensor<1x154x1xf16>' and 'tensor<1xf32>' are not broadcast compatible
LLVM ERROR: Failed to infer result type(s).

this is the code

from diffusers import DiffusionPipeline
import torch

pipe_prior = DiffusionPipeline.from_pretrained("kandinsky-community/kandinsky-2-1-prior", torch_dtype=torch.float16)"mps")

t2i_pipe = DiffusionPipeline.from_pretrained("kandinsky-community/kandinsky-2-1", torch_dtype=torch.float16)"mps")

prompt = "A purple panda playing soccer, claymation, cinematic, sunny"
negative_prompt = "low quality, bad quality"

generator = torch.Generator(device="mps").manual_seed(12)
image_embeds, negative_image_embeds = pipe_prior(prompt, negative_prompt, guidance_scale=1.0, generator=generator).to_tuple()

image = t2i_pipe(prompt, negative_prompt=negative_prompt, image_embeds=image_embeds, negative_image_embeds=negative_image_embeds).images[0]"purple_soccer_panda.png")

Sign up or log in to comment