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metadata
license: creativeml-openrail-m
base_model: ekshat/stable-diffusion-anime-style
datasets:
  - lambdalabs/naruto-blip-captions
tags:
  - stable-diffusion
  - stable-diffusion-diffusers
  - text-to-image
  - diffusers
inference: true

Text-to-image finetuning - ekshat/Stable_Diffussion_Anime_Style

This pipeline was finetuned from ekshat/stable-diffusion-anime-style on the lambdalabs/naruto-blip-captions dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['A person with blue eyes.']:

val_imgs_grid

Pipeline usage

You can use the pipeline like so:

from diffusers import DiffusionPipeline
import torch

pipeline = DiffusionPipeline.from_pretrained("ekshat/Stable_Diffussion_Anime_Style", torch_dtype=torch.float16)
pipeline = pipeline.to("cuda")

prompt = "A person with blue eyes."
image = pipeline(prompt).images[0]
image.save("my_image.png")

Training info

These are the key hyperparameters used during training:

  • Epochs: 17
  • Learning rate: 2e-06
  • Batch size: 2
  • Gradient accumulation steps: 1
  • Image resolution: 512
  • Mixed-precision: fp16