Text-to-Image
Diffusers
UniDiffuserPipeline
image-to-text
image-captioning
image-variation
text-variation
multi-modality
generative model
Instructions to use dg845/unidiffuser-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dg845/unidiffuser-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dg845/unidiffuser-diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
| { | |
| "_class_name": "UniDiffuserPipeline", | |
| "_diffusers_version": "0.21.0.dev0", | |
| "clip_image_processor": [ | |
| "transformers", | |
| "CLIPImageProcessor" | |
| ], | |
| "clip_tokenizer": [ | |
| "transformers", | |
| "CLIPTokenizer" | |
| ], | |
| "image_encoder": [ | |
| "transformers", | |
| "CLIPVisionModelWithProjection" | |
| ], | |
| "scheduler": [ | |
| "diffusers", | |
| "DPMSolverMultistepScheduler" | |
| ], | |
| "text_decoder": [ | |
| "unidiffuser", | |
| "UniDiffuserTextDecoder" | |
| ], | |
| "text_encoder": [ | |
| "transformers", | |
| "CLIPTextModel" | |
| ], | |
| "text_tokenizer": [ | |
| "transformers", | |
| "GPT2Tokenizer" | |
| ], | |
| "unet": [ | |
| "unidiffuser", | |
| "UniDiffuserModel" | |
| ], | |
| "vae": [ | |
| "diffusers", | |
| "AutoencoderKL" | |
| ] | |
| } | |