Text-to-image finetuning - linhqyy/sd-pokemon-15k-model
This pipeline was finetuned from CompVis/stable-diffusion-v1-4 on the lambdalabs/pokemon-blip-captions dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['cute hippo']:
Pipeline usage
You can use the pipeline like so:
from diffusers import DiffusionPipeline
import torch
pipeline = DiffusionPipeline.from_pretrained("linhqyy/sd-pokemon-15k-model", torch_dtype=torch.float16)
prompt = "cute hippo"
image = pipeline(prompt).images[0]
image.save("my_image.png")
Training info
These are the key hyperparameters used during training:
- Epochs: 72
- Learning rate: 1e-05
- Batch size: 1
- Gradient accumulation steps: 4
- 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
CompVis/stable-diffusion-v1-4