Text-to-Image
Diffusers
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
dreambooth-hackathon
food
Instructions to use jnick/chicken-tikka-masala with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jnick/chicken-tikka-masala with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jnick/chicken-tikka-masala", dtype=torch.bfloat16, device_map="cuda") prompt = "ctm curry dish in a rustic modern farmhouse kitchen" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
DreamBooth model for the ctm concept trained by jnick on the jnick/chicken-tikka-masala dataset.
This is a Stable Diffusion model fine-tuned on the ctm concept with DreamBooth. It can be used by modifying the instance_prompt: a photo of ctm curry dish
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 images of chicken tikka masala for the food theme. Here are some examples:
| "a delicious plate of ctm curry dish in the Grand Canyon" | "ctm curry dish in a modern science laboratory" |
|---|---|
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Usage
from diffusers import StableDiffusionPipeline
pipeline = StableDiffusionPipeline.from_pretrained('jnick/chicken-tikka-masala')
image = pipeline().images[0]
image
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