Image-to-Text
Diffusers
Safetensors
PyTorch
StableDiffusionPipeline
stable-diffusion
text-to-image
diffusion-models-class
dreambooth-hackathon
bedroom
Instructions to use gaurav761/bedroom5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use gaurav761/bedroom5 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("gaurav761/bedroom5", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of room bed, wall, table, curtains in the Acropolis, based on the input image" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
DreamBooth model for the room concept trained by gaurav761 on the gaurav761/bedroom-image dataset.
This is a Stable Diffusion model fine-tuned on the room concept with DreamBooth. It can be used by modifying the instance_prompt: a photo of room bed, wall, table, curtains
This model was created as part of the DreamBooth Hackathon 🔥. Visit the organisation page for instructions on how to take part!
Description
This is a Stable Diffusion model fine-tuned on bed, wall, table, curtains images for the bedroom theme.
Usage
from diffusers import StableDiffusionPipeline
pipeline = StableDiffusionPipeline.from_pretrained('gaurav761/bedroom5')
image = pipeline().images[0]
image
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