    
# Text-to-image finetuning - gremlin97/runs3

This pipeline was finetuned from **runwayml/stable-diffusion-v1-5** on the **None** dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['A photo of a crop field']: 

![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("gremlin97/runs3", torch_dtype=torch.float16)
prompt = "A photo of a crop field"
image = pipeline(prompt).images[0]
image.save("my_image.png")
```

## Training info

These are the key hyperparameters used during training:

* Epochs: 7
* Learning rate: 1e-05
* Batch size: 1
* Gradient accumulation steps: 4
* Image resolution: 512
* Mixed-precision: fp16


{"license": "creativeml-openrail-m", "tags": ["stable-diffusion", "stable-diffusion-diffusers", "text-to-image", "diffusers"], "datasets": ["None"], "base_model": "runwayml/stable-diffusion-v1-5", "inference": true}
diffusers tensorboard safetensors stable-diffusion stable-diffusion-diffusers text-to-image dataset:None base_model:runwayml/stable-diffusion-v1-5 license:creativeml-openrail-m endpoints_compatible diffusers:StableDiffusionPipeline region:us