diffusers tensorboard safetensors stable-diffusion stable-diffusion-diffusers text-to-image dataset:peterholdsworth/AND base_model:CompVis/stable-diffusion-v1-2 license:creativeml-openrail-m autotrain_compatible endpoints_compatible diffusers:StableDiffusionPipeline region:us

---
license: creativeml-openrail-m
base_model: CompVis/stable-diffusion-v1-2
datasets:
- peterholdsworth/AND
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
inference: true
---
    
# Text-to-image finetuning - peterholdsworth/output2

This pipeline was finetuned from **CompVis/stable-diffusion-v1-2** on the **peterholdsworth/AND** dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['Please draw a mug with an ANDlogo logo']: 

![val_imgs_grid](./val_imgs_grid.png)


## Pipeline usage

You can use the pipeline like so:

```python
from diffusers import DiffusionPipeline
import torch

pipeline = DiffusionPipeline.from_pretrained("peterholdsworth/output2", torch_dtype=torch.float16)
prompt = "Please draw a mug with an ANDlogo logo"
image = pipeline(prompt).images[0]
image.save("my_image.png")
```

## Training info

These are the key hyperparameters used during training:

* Epochs: 400
* Learning rate: 1e-05
* Batch size: 1
* Gradient accumulation steps: 4
* Image resolution: 512
* Mixed-precision: fp16

