Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
stable-diffusion
dalle
mj
dreamdrop
openskyml
Instructions to use ehristoforu/dreamdrop with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ehristoforu/dreamdrop with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ehristoforu/dreamdrop", dtype=torch.bfloat16, device_map="cuda") prompt = "epic realistic, faded, ((neutral colors)), art, (hdr:1.5), (muted colors:1.2), pastel, hyperdetailed, (artstation:1.5), warm lights, dramatic light, (intricate details:1.2), vignette, complex background, rutkowski" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
| { | |
| "_class_name": "StableDiffusionPipeline", | |
| "_diffusers_version": "0.25.0", | |
| "feature_extractor": [ | |
| "transformers", | |
| "CLIPFeatureExtractor" | |
| ], | |
| "image_encoder": [ | |
| null, | |
| null | |
| ], | |
| "scheduler": [ | |
| "diffusers", | |
| "PNDMScheduler" | |
| ], | |
| "text_encoder": [ | |
| "transformers", | |
| "CLIPTextModel" | |
| ], | |
| "tokenizer": [ | |
| "transformers", | |
| "CLIPTokenizer" | |
| ], | |
| "unet": [ | |
| "diffusers", | |
| "UNet2DConditionModel" | |
| ], | |
| "vae": [ | |
| "diffusers", | |
| "AutoencoderKL" | |
| ] | |
| } | |