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.
- Downloads last month
- 7
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for linhqyy/sd-pokemon-15k-cp-model
Base model
CompVis/stable-diffusion-v1-4