Text-to-Image
Diffusers
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
dreambooth-hackathon
landscape
Instructions to use hasarinduperera/sinha-rock with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hasarinduperera/sinha-rock with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hasarinduperera/sinha-rock", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of sinha rock in the Kingdom of Greece" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
DreamBooth model for the sinha (Sigiriya rock) concept trained by hasarinduperera on the hasarinduperera/sigiriya-image-dataset dataset.
This is a Stable Diffusion model fine-tuned on the sinha (Sigiriya rock) concept with DreamBooth. It can be used by modifying the instance_prompt: a photo of sinha rock
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 Sigiriya rock images for the landscape theme.
Usage
from diffusers import StableDiffusionPipeline
pipeline = StableDiffusionPipeline.from_pretrained('hasarinduperera/sinha-rock')
image = pipeline().images[0]
image
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