diffusers tensorboard safetensors stable-diffusion stable-diffusion-diffusers text-to-image dataset:GabrielGaleana34/Products base_model:stabilityai/stable-diffusion-2-1 license:creativeml-openrail-m autotrain_compatible endpoints_compatible diffusers:StableDiffusionPipeline region:us

---
license: creativeml-openrail-m
base_model: stabilityai/stable-diffusion-2-1
datasets:
- GabrielGaleana34/Products
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
inference: true
---
    
# Text-to-image finetuning - GabrielGaleana34/sd-model-finetuned

This pipeline was finetuned from **stabilityai/stable-diffusion-2-1** on the **GabrielGaleana34/Products** dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['[A Coca-cola soda in a plastic bottle]']: 

![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("GabrielGaleana34/sd-model-finetuned", torch_dtype=torch.float16)
prompt = "A Coca-cola soda in a plastic bottle"
image = pipeline(prompt).images[0]
image.save("my_image.png")
```

## Training info

These are the key hyperparameters used during training:

* Epochs: 89
* Learning rate: 1e-06
* Batch size: 1
* Gradient accumulation steps: 4
* Image resolution: 1024
* Mixed-precision: fp16

