LoRA Finetuning - dongOi071102/wuerstchen-prior-meme-lora-4
This pipeline was finetuned from warp-ai/wuerstchen-prior on the dongOi071102/meme-pretreatment-dataset dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['a catton cat with angry face']:
Pipeline usage
You can use the pipeline like so:
from diffusers import DiffusionPipeline
import torch
pipeline = AutoPipelineForText2Image.from_pretrained(
"warp-ai/wuerstchen", torch_dtype=float32
)
# load lora weights from folder:
pipeline.prior_pipe.load_lora_weights("dongOi071102/wuerstchen-prior-meme-lora-4", torch_dtype=float32)
image = pipeline(prompt=prompt).images[0]
image.save("my_image.png")
Training info
These are the key hyperparameters used during training:
- LoRA rank: 4
- Epochs: 100
- Learning rate: 0.0001
- Batch size: 8
- Gradient accumulation steps: 1
- Image resolution: 512
- Mixed-precision: fp16
More information on all the CLI arguments and the environment are available on your wandb
run page.
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Base model
warp-ai/wuerstchen-prior