Instructions to use noema-art/impresstation-zimage with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use noema-art/impresstation-zimage with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Tongyi-MAI/Z-Image", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("noema-art/impresstation-zimage") prompt = "stationthis, stationthis, low poly playstation screenshot style, A determined young woman with fiery red pigtails tied…" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
| # ai-toolkit zimage LoRA — generated by the crystal training modus. | |
| # name=impresstation-zimage trigger=stationthis dataset=dataset steps=3000 | |
| job: extension | |
| config: | |
| name: "impresstation-zimage" | |
| process: | |
| - type: 'ui_trainer' | |
| sqlite_db_path: "/aitk/aitk_db.db" | |
| training_folder: "/aitk/output" | |
| device: cuda:0 | |
| trigger_word: "stationthis" | |
| network: | |
| type: "lora" | |
| linear: 32 | |
| linear_alpha: 32 | |
| save: | |
| dtype: float16 | |
| save_every: 250 | |
| max_step_saves_to_keep: 4 | |
| push_to_hub: false | |
| datasets: | |
| - folder_path: "dataset" | |
| caption_ext: "txt" | |
| caption_dropout_rate: 0.05 | |
| resolution: [ 512, 768, 1024 ] | |
| train: | |
| batch_size: 1 | |
| steps: 3000 | |
| gradient_accumulation: 1 | |
| train_unet: true | |
| train_text_encoder: false | |
| gradient_checkpointing: true | |
| noise_scheduler: "flowmatch" | |
| timestep_type: "weighted" | |
| optimizer: "adamw8bit" | |
| lr: 0.0001 | |
| optimizer_params: | |
| weight_decay: 1e-5 | |
| ema_config: | |
| use_ema: false | |
| ema_decay: 0.99 | |
| dtype: bf16 | |
| model: | |
| name_or_path: "Tongyi-MAI/Z-Image" | |
| arch: "zimage" | |
| quantize: true | |
| quantize_te: true | |
| low_vram: true | |
| qtype: "qfloat8" | |
| model_kwargs: | |
| match_target_res: false | |
| sample: | |
| sampler: "flowmatch" | |
| sample_every: 3000 | |
| width: 1024 | |
| height: 1024 | |
| prompts: | |
| - "[trigger], stationthis, low poly playstation screenshot style, A determined young woman with fiery red pigtails tied with yellow bands stands confidently in a grassy outdoor area, her hands on her hips as she gazes forward, wearing a white blouse with a red bow and dark skirt. Behind her, a stone wall and a simple wooden platform suggest a rustic, possibly medieval or fantasy setting, while a small compass-like UI element in the corner hints at navigation or exploration within the game world." | |
| - "[trigger], stationthis, low poly playstation screenshot style, Under a misty, twilight sky, a male adventurer in blue and white armor stands poised with a sword, facing a female companion in a red tunic who holds a staff, as they navigate a stone-paved bridge lined with arched colonnades and palm trees, with distant buildings glowing softly in the foggy background." | |
| - "[trigger], stationthis, low poly playstation screenshot style, A stoic, sunglasses-wearing man in a denim jacket stands in the bustling streets of a sunlit city, his gaze fixed upward as towering skyscrapers loom behind him, their windows reflecting the bright sky. The scene is framed from a low-angle perspective, emphasizing the urban scale, with a mini-map and cash balance visible in the corner, hinting at a world of action and choice." | |
| - "[trigger], stationthis, low poly playstation screenshot style, A stern, determined woman with a black headband and tactical jacket stands in a dim, misty forest, her gaze locked forward as if challenging the viewer, with the ominous subtitle “Think you can pull the trigger?” hinting at an impending confrontation. The camera holds steady on her face, framing her in the gloom of tangled trees and shadowy undergrowth, emphasizing the tension and isolation of the moment." | |
| neg: "" | |
| seed: 42 | |
| walk_seed: true | |
| guidance_scale: 4 | |
| sample_steps: 25 | |
| meta: | |
| name: "[name]" | |
| version: '1.0' | |