import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("bghira/pseudo-journey", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Deprecation notice
This model was a research project focused on the effect of fine-tuning the OpenCLIP text encoder.
It has been deprecated in favour of a newer checkpoint that continued training this model.
This model remains accessible as a test comparison and possible base model for fine-tuning.
Training data
Base model: stabilityai/stable-diffusion-2-1
Data: 3300 midjourney 5.1 upscaled images with their captions.
Training parameters
Duration: 4000 steps LR scheduler: polynomial Batch size: 3 Text encoder: Thawed Optimizer: 8bit ADAM No prior loss preservation
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