Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
dreambooth
diffusers-training
stable-diffusion
stable-diffusion-diffusers
lora
Instructions to use Colezwhy/dreambooth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Colezwhy/dreambooth with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Colezwhy/dreambooth") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Ctrl+K
- checkpoint-100
- checkpoint-1000
- checkpoint-200
- checkpoint-300
- checkpoint-400
- checkpoint-500
- checkpoint-600
- checkpoint-700
- checkpoint-800
- checkpoint-900
- feature_extractor
- logs
- safety_checker
- scheduler
- text_encoder
- tokenizer
- unet
- vae
- 1.52 kB
- 151 MB xet
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- 432 kB
- 693 Bytes
- 3.23 MB xet