Instructions to use onkarsus13/UniDFlow14B_Pref with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use onkarsus13/UniDFlow14B_Pref with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("onkarsus13/UniDFlow14B_Pref", 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
| { | |
| "_class_name": "UniDFlowPipeline", | |
| "_diffusers_version": "0.37.1", | |
| "_name_or_path": "black-forest-labs/FLUX.2-klein-base-9B", | |
| "is_distilled": false, | |
| "scheduler": [ | |
| "diffusers", | |
| "FlowMatchEulerDiscreteScheduler" | |
| ], | |
| "text_encoder": [ | |
| "transformers", | |
| "Qwen3ForCausalLM" | |
| ], | |
| "tokenizer": [ | |
| "transformers", | |
| "Qwen2Tokenizer" | |
| ], | |
| "transformer": [ | |
| "models.transformer_unidflow", | |
| "UniDFlowTransformer2DModel" | |
| ], | |
| "vae": [ | |
| "models.vae", | |
| "AutoencoderKLUniDFlow" | |
| ] | |
| } | |