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---
tags:
- pytorch
- diffusers
- stable-diffusion
- text-to-image
- diffusion-models-class
- dreambooth-hackathon
---
# DreamBooth model for the groot concept traine on the LinoyTsaban/dreambooth-hackathon-images-groot dataset.
This is a Stable Diffusion model fine-tuned on the groot concept with DreamBooth. It can be used by modifying the `instance_prompt`: groot figurine
This model was created as part of the DreamBooth Hackathon 🔥. Visit the [organisation page](https://huggingface.co/dreambooth-hackathon) for instructions on how to take part!
params used:
scheduler- DDIMScheduler
resolution=512
learning_rate=2e-06
max_train_steps= 500
train_batch_size=1
gradient_accumulation_steps=2
max_grad_norm=1.0
gradient_checkpointing=True
use_8bit_adam=True
seed=14071995,
sample_batch_size=2
## Usage
```python
from diffusers import StableDiffusionPipeline
pipeline = StableDiffusionPipeline.from_pretrained('LinoyTsaban/dreambooth-groot')
name_of_concept = "groot"
type_of_thing = "figurine"
prompt = f"a photo of groot figurine in the Louvre museum"
# Tune the guidance to control how closely the generations follow the prompt.
# Values between 7-11 usually work best
guidance_scale = 8 #
image = pipeline(prompt, guidance_scale=guidance_scale).images[0]
image
```
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