zhangyi617/sd14_naruto_full_finetune_0.005

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Text-to-image finetuning - zhangyi617/sd14narutofullfinetune0.005

This pipeline was finetuned from CompVis/stable-diffusion-v1-4 on the lambdalabs/naruto-blip-captions dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['a car is driving down the road with another car']:

[image]

Pipeline usage

You can use the pipeline like so:

from diffusers import DiffusionPipeline
import torch

pipeline = DiffusionPipeline.from_pretrained("zhangyi617/sd14_naruto_full_finetune_0.005", torch_dtype=torch.float16)
prompt = "a car is driving down the road with another car"
image = pipeline(prompt).images[0]
image.save("my_image.png")

Training info

These are the key hyperparameters used during training:

• —Epochs: 20
• —Learning rate: 0.0001
• —Batch size: 4
• —Gradient accumulation steps: 1
• —Image resolution: 512
• —Mixed-precision: fp16

Intended uses & limitations

How to use

# TODO: add an example code snippet for running this diffusion pipeline

Limitations and bias

[TODO: provide examples of latent issues and potential remediations]

Training details

[TODO: describe the data used to train the model]