---
base_model: runwayml/stable-diffusion-v1-5
library_name: diffusers
license: creativeml-openrail-m
tags:
- text-to-image
- dreambooth
- diffusers-training
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- dreambooth
- diffusers-training
- stable-diffusion
- stable-diffusion-diffusers
inference: true
instance_prompt: a photo of can on the table
---

<!-- This model card has been generated automatically according to the information the training script had access to. You
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# DreamBooth - FQiao/output

This is a dreambooth model derived from runwayml/stable-diffusion-v1-5. The weights were trained on a photo of can on the table using [DreamBooth](https://dreambooth.github.io/).
You can find some example images in the following. 



DreamBooth for the text encoder was enabled: False.


## Intended uses & limitations

#### How to use

```python
from diffusers import AutoPipelineForText2Image
import torch

pipeline = AutoPipelineForText2Image.from_pretrained("FQiao/DreamboothCan", torch_dtype=torch.float16).to("cuda")
prompt = "a photo of can on the desk"
image = pipeline(prompt).images[0]
image
```

#### Limitations and bias

[TODO: provide examples of latent issues and potential remediations]

## Training details

[TODO: describe the data used to train the model]