Text-to-image finetuning - yeonsikc/vae_conist40k_fp16
This pipeline was finetuned from runwayml/stable-diffusion-v1-5 on the yeonsikc/conist40k dataset. Below are some example images generated with the finetuned pipeline using the following prompts: Nothing:
Pipeline usage
You can use the pipeline like so:
from diffusers import DiffusionPipeline
import torch
pipeline = DiffusionPipeline.from_pretrained("yeonsikc/vae_conist40k_fp16", torch_dtype=torch.float16)
image = pipeline(prompt).images[0]
image.save("my_image.png")
Training info
These are the key hyperparameters used during training:
- Epochs: 2000
- Learning rate: 5.76e-06
- Batch size: 8
- Gradient accumulation steps: 2
- Image resolution: 512
- Mixed-precision: None
More information on all the CLI arguments and the environment are available on your wandb run page.
