diffusers safetensors stable-diffusion stable-diffusion-diffusers text-to-image dataset:None license:creativeml-openrail-m autotrain_compatible endpoints_compatible diffusers:StableDiffusionPipeline region:us

---
license: creativeml-openrail-m
base_model: /shared/s1/lab06/wonyoung/diffusers/CXR_ti_nf
datasets:
- None
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
inference: true
---
    
# Text-to-image finetuning - Stomper10/CXR_unet_profile2

This pipeline was finetuned from **/shared/s1/lab06/wonyoung/diffusers/CXR_ti_nf** on the **None** dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['A photo of a lung-xray.']: 

![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("Stomper10/CXR_unet_profile2", torch_dtype=torch.float16)
prompt = "A photo of a lung-xray."
image = pipeline(prompt).images[0]
image.save("my_image.png")
```

## Training info

These are the key hyperparameters used during training:

* Epochs: 1
* Learning rate: 0.00128
* Batch size: 32
* Gradient accumulation steps: 1
* Image resolution: 512
* Mixed-precision: fp16


More information on all the CLI arguments and the environment are available on your [`wandb` run page](https://wandb.ai/jwy4888/text2image-fine-tune/runs/4k6bikv2).
