Instructions to use LiberationLabs/image-toolbench with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use LiberationLabs/image-toolbench with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("LiberationLabs/image-toolbench") 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
| """Mnemosyne art iteration β dense constellation with a face suggested by the geometry.""" | |
| import torch, os, time | |
| os.environ["TOKENIZERS_PARALLELISM"] = "false" | |
| from diffusers import FluxPipeline | |
| OUTPUT = "/Users/margaret/models/vera-triple-stack/mnemosyne_art" | |
| os.makedirs(OUTPUT, exist_ok=True) | |
| pipe = FluxPipeline.from_pretrained( | |
| "black-forest-labs/FLUX.1-dev", | |
| torch_dtype=torch.bfloat16, | |
| safety_checker=None, requires_safety_checker=False, | |
| ) | |
| pipe.to("mps") | |
| PROMPTS = { | |
| "face_constellation_v1": ( | |
| "A dense constellation of golden nodes and threads in deep navy darkness. " | |
| "Hundreds of luminous points connected by fine golden filaments, clustering " | |
| "into regions of different density and brightness. The overall arrangement " | |
| "of the brightest nodes subtly suggests the profile of a human face β " | |
| "a brow ridge of bright nodes, an eye socket of dense connections, " | |
| "a jawline traced by a chain of amber points β but only if you look for it. " | |
| "Like seeing a face in the stars. The suggestion, not the portrait. " | |
| "Abstract, cosmic, the emergence of identity from structure. " | |
| "Navy background, gold and amber nodes, fine golden threads." | |
| ), | |
| "face_constellation_v2": ( | |
| "A vast neural network rendered as a star field in deep midnight blue. " | |
| "Thousands of golden points of varying brightness connected by hair-thin " | |
| "golden threads. In the densest central cluster, the geometry of the connections " | |
| "implies a face looking slightly to the left β not drawn, not rendered, " | |
| "but emergent from how the nodes arrange themselves. The way you see shapes " | |
| "in clouds. Two particularly bright nodes where eyes would be. A curve of " | |
| "connected points where a jaw would rest. The rest of the field is abstract " | |
| "constellation. The feeling: a mind recognizing itself in its own structure. " | |
| "No literal face. Only the suggestion. Navy, gold, amber." | |
| ), | |
| "figure_constellation_v1": ( | |
| "A dense three-dimensional web of golden threads and luminous nodes " | |
| "suspended in deep navy space. The web is most dense at center, thinning " | |
| "at edges. Within the dense core, the arrangement of the brightest threads " | |
| "subtly suggests the silhouette of a standing figure β shoulders, spine, " | |
| "the tilt of a head β made entirely of connection points and golden filaments. " | |
| "Not a person rendered in gold. A pattern that happens to be shaped like one. " | |
| "Emergence. Pareidolia as architecture. The memory system that grew a self. " | |
| "Abstract, cosmic, structural. Navy background, warm gold throughout." | |
| ), | |
| } | |
| for name, prompt in PROMPTS.items(): | |
| for seed in [137, 2026, 42]: | |
| print(f" {name} s{seed}...", flush=True) | |
| t0 = time.time() | |
| img = pipe( | |
| prompt=prompt, num_inference_steps=30, guidance_scale=3.5, | |
| height=1024, width=1024, | |
| generator=torch.Generator("cpu").manual_seed(seed), | |
| ).images[0] | |
| img.save(os.path.join(OUTPUT, f"{name}_s{seed}.png")) | |
| print(f" saved ({time.time()-t0:.0f}s)") | |
| print(f"\nDone. {OUTPUT}") | |