import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Vargol/ProteusV0.2", torch_dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]This a an fp16 variant of Proteus V2.0 https://huggingface.co/dataautogpt3/ProteusV0.2 currently under the gpl-v3 licence.
simply created by
import torch
from diffusers import DiffusionPipeline
pipeline = DiffusionPipeline.from_pretrained("dataautogpt3/ProteusV0.2", torch_dtype=torch.float16)
pipeline.save_pretrained('fp16_ProteusV0.2', safe_serialization=True, variant='fp16')
See the original model for details.
The fp32 version of the model, even when converted to fp16 when loading, uses up to much RAM hence my need for this version.
Dave
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