Text-to-Image
Diffusers
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
dreambooth-hackathon
animal
Instructions to use mathpn/dreambooth-friendly-otter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mathpn/dreambooth-friendly-otter with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mathpn/dreambooth-friendly-otter", dtype=torch.bfloat16, device_map="cuda") prompt = "an ött3r otter flying over a city at night, neon lights, highly detailed, digital painting, artstation, concept art, sharp focus, illustration, art by artgerm and greg rutkowski and alphonse mucha, cinematic lighting" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 0fa7b09e1d588157a6a1797f69c921c0ed525962f2c946a86feede7fe4457259
- Size of remote file:
- 335 MB
- SHA256:
- f3d17aa398e021a2600c4a8b570060056a069a1b7b6f8ace78ffa52fff69395d
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