README.md

---
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](./val-img.jpg)


## Pipeline usage

You can use the pipeline like so:

```python
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