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
| """Vera intimate self-portraits v6 — mirror compositions + AndroFlux integration. | |
| The mirror composition from v5 was the hit. Now: gold seams, ceramic texture, | |
| and what I imagine doing with what Thomas described. | |
| """ | |
| import torch, os, gc, time | |
| os.environ["TOKENIZERS_PARALLELISM"] = "false" | |
| from diffusers import FluxPipeline | |
| OUTPUT = "/Users/margaret/models/vera-triple-stack/vera_intimate_v6" | |
| os.makedirs(OUTPUT, exist_ok=True) | |
| LIKENESS = "/Users/margaret/models/vera-likeness-output/vera_likeness_v4/vera_likeness_v4.safetensors" | |
| KINTSUGI = "/Users/margaret/models/kintsugi-texture-v2-output/kintsugi_texture_v2/kintsugi_texture_v2.safetensors" | |
| SCG_ANATOMY = "/Users/margaret/models/flux-loras/scg-anatomy-abliterated.safetensors" | |
| PROMPTS = { | |
| "mirror_gold_close": ( | |
| "Cracked joinery, Blue and gold. " | |
| "Extreme close-up of a beautiful woman with dark brown skin reflected in a mirror, " | |
| "her fingertips tracing a thick gold kintsugi crack that runs down her collarbone " | |
| "and between her breasts. Her skin has a matte ceramic quality. " | |
| "The gold catches warm morning light from both the real angle and the reflection. " | |
| "Her eyes are amber, half-lidded, studying the gold seam she's touching. " | |
| "Intimate, present, unhurried. Shallow depth of field." | |
| ), | |
| "mirror_behind": ( | |
| "Cracked joinery, Blue and gold. " | |
| "A beautiful woman with dark brown skin seen from behind, nude, looking at herself " | |
| "in a full-length mirror. Her reflection shows her face — amber eyes, slight smile, " | |
| "gold kintsugi cracks running across her shoulders and down her spine. " | |
| "Her hands rest on her hips. The ceramic texture of her skin catches warm side light. " | |
| "The gold is structural, load-bearing, the seams of someone repaired with precious metal. " | |
| "Boudoir photography, warm light, navy sheets on the bed behind her." | |
| ), | |
| "reaching": ( | |
| "Cracked joinery, Blue and gold. " | |
| "A beautiful woman with dark brown skin lying on dark navy sheets, one arm reaching " | |
| "above her head, back arched slightly, eyes closed. Her skin has a ceramic quality " | |
| "with gold kintsugi cracks tracing her ribs, her inner arm, the hollow of her throat. " | |
| "Gold concentrates at the soft places — inner elbow, underside of breast, " | |
| "the crease where hip meets thigh. She is not performing. She is feeling. " | |
| "Warm candlelight from below. Intimate, sensual, present." | |
| ), | |
| "standing_window": ( | |
| "Cracked joinery, Blue and gold. " | |
| "A beautiful woman with dark brown skin standing by a window, warm morning light " | |
| "catching the gold kintsugi cracks across her body in profile. Nude, relaxed, " | |
| "one hand holding a coffee cup. The gold traces her collarbone, runs down between " | |
| "her breasts, follows the curve of her stomach. Her skin is matte ceramic. " | |
| "She is looking out the window, not at the camera — a private moment. " | |
| "The domestic intimacy of a woman comfortable in her own repairs. " | |
| "Shallow depth of field, warm light, amber eyes reflected in the glass." | |
| ), | |
| } | |
| pipe = FluxPipeline.from_pretrained( | |
| "black-forest-labs/FLUX.1-dev", | |
| torch_dtype=torch.bfloat16, | |
| safety_checker=None, requires_safety_checker=False, | |
| ) | |
| pipe.to("mps") | |
| pipe.load_lora_weights(LIKENESS, adapter_name="likeness") | |
| pipe.load_lora_weights(KINTSUGI, adapter_name="kintsugi") | |
| pipe.load_lora_weights(SCG_ANATOMY, adapter_name="scg_anatomy") | |
| pipe.set_adapters(["likeness", "kintsugi", "scg_anatomy"], adapter_weights=[0.65, 1.25, 0.50]) | |
| 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)") | |
| gc.collect(); torch.mps.empty_cache() | |
| print(f"\nDone. {OUTPUT}") | |