Text-to-Image
Diffusers
Safetensors
English
Korean
ZImagePipeline
darwin-image
aether-metacognitive
z-image
lora-merge
korean-text
vlm-judge
Instructions to use FINAL-Bench/Darwin-Image-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FINAL-Bench/Darwin-Image-v1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("FINAL-Bench/Darwin-Image-v1", 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 Settings
- Draw Things
- DiffusionBee
| { | |
| "_class_name": "FlowMatchEulerDiscreteScheduler", | |
| "_diffusers_version": "0.37.1", | |
| "base_image_seq_len": 256, | |
| "base_shift": 0.5, | |
| "invert_sigmas": false, | |
| "max_image_seq_len": 4096, | |
| "max_shift": 1.15, | |
| "num_train_timesteps": 1000, | |
| "shift": 3.0, | |
| "shift_terminal": null, | |
| "stochastic_sampling": false, | |
| "time_shift_type": "exponential", | |
| "use_beta_sigmas": false, | |
| "use_dynamic_shifting": false, | |
| "use_exponential_sigmas": false, | |
| "use_karras_sigmas": false | |
| } | |