Instructions to use fyp-admin/dreambooth_Venus_15 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fyp-admin/dreambooth_Venus_15 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("fyp-admin/dreambooth_Venus_15") prompt = "a picture of planet Venus in the center, in golden orange color and white hues on the poles. It is present in space which has dark background, embedded with a cluster of small-sized bright stars." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
LoRA DreamBooth - fyp-admin/dreambooth_Venus_15
These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were trained on a picture of planet Venus in the center, in golden orange color and white hues on the poles. It is present in space which has dark background, embedded with a cluster of small-sized bright stars. using DreamBooth. You can find some example images in the following.
LoRA for the text encoder was enabled: False.
Intended uses & limitations
How to use
# TODO: add an example code snippet for running this diffusion pipeline
Limitations and bias
[TODO: provide examples of latent issues and potential remediations]
Training details
[TODO: describe the data used to train the model]
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Model tree for fyp-admin/dreambooth_Venus_15
Base model
runwayml/stable-diffusion-v1-5


