Text-to-Image
Diffusers
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
dreambooth-hackathon
animal
Instructions to use Nlpeva/flufflemarkednoser-cat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Nlpeva/flufflemarkednoser-cat with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Nlpeva/flufflemarkednoser-cat", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of flufflemarkednoser cat in the bookstore" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
DreamBooth model for the flufflemarkednoser concept trained by Nlpeva on the Nlpeva/Calico_fluffy dataset.
This is a Stable Diffusion model fine-tuned on the flufflemarkednoser concept with DreamBooth. It can be used by modifying the instance_prompt: a photo of flufflemarkednoser cat
This model was created as part of the DreamBooth Hackathon ๐ฅ. Visit the organisation page for instructions on how to take part!
Description
This is a Stable Diffusion model fine-tuned on cat images for the animal theme. It is based on ten images of a calico cat. It works well for phrases like on the moon and at the beach. The cat, Sharpie, was called that because of her distinctive black nose that looks like someone drew on it with a permanent marker.
Usage
from diffusers import StableDiffusionPipeline
pipeline = StableDiffusionPipeline.from_pretrained('Nlpeva/flufflemarkednoser-cat')
image = pipeline().images[0]
image
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