KiwiMate 1.0
Collection
6 items • Updated
import torch
from diffusers import DiffusionPipeline
from diffusers.utils import load_image
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.2-klein-9B", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("KiwiMate/KiwiMate-Image-Fast-1.0")
prompt = "Turn this cat into a dog"
input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
image = pipe(image=input_image, prompt=prompt).images[0]KiwiMate Image Fast 1.0
A speed-tuned fine-tune of black-forest-labs/FLUX.2-klein-9B, trained with ai-toolkit to produce clean, sharp images in very few steps.
Image inputs supported — like its base model, this fine-tune can take images as inputs, so you can drive generation with reference photos, restyle or edit your own pictures, and do full image-to-image workflows, not just text-to-image.
What's in the repo
| File | Description |
|---|---|
KiwiMate-Image-Fast-1.0-merged.safetensors |
Standalone merged checkpoint (~17 GB). Drop into models/checkpoints and run — no base model needed. |
KiwiMate-Image-Fast-1.0.safetensors |
Final LoRA adapter (step 3000, rank 32, ~158 MB). Apply on top of the original flux-2-klein-9b checkpoint at full strength. |
checkpoints/ |
Intermediate LoRA checkpoints every 250 steps (250–2500), if you want an earlier snapshot. |
merge_lora.py |
Dependency-light script used to merge the LoRA into the base checkpoint (numpy only, streams tensor-by-tensor, resumable). |
Sample gallery
All samples below were generated by the final step-3000 weights.
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| Prompt-driven scene: chess picnic with a fireball behind (color) | Monochrome café portrait, bokeh, holding coffee cup | Fisheye horse DJ at the decks under a disco ball | Beach guy giving thumbs-up next to a leaping shark |
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| Cozy log cabin deep in snow-capped mountains | High-energy live rock singer on stage (B&W) | Craftsman hand-repairing a chair in his workshop (B&W) | Clean studio fashion shot on white seamless background |
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| Text rendering: "thiss is a sign" held up in grainy monochrome | Sepia bulldog riding a chopper across the dunes | Neon KiwiMate storefront glowing on a rainy night | Bird soaring over misty peaks, ink-wash style (B&W) |
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| Split-track commuter trains meeting head-on (B&W) |
The set shows off speed-friendly fundamentals: good anatomy (hands, faces, animals), legible signage/text, strong lighting (stage rays, neon reflections), stylized monochrome looks, and larger scenes that hold detail without burning many sampling steps.
Usage
ComfyUI:
# Merged checkpoint — drag straight into models/checkpoints
huggingface-cli download KiwiMate/KiwiMate-Image-Fast-1.0 KiwiMate-Image-Fast-1.0-merged.safetensors --local-dir models/checkpoints
Or stack the adapter on the unmodified base instead:
# Standalone LoRA on top of black-forest-labs/FLUX.2-klein-9B at strength ~1.0
huggingface-cli download KiwiMate/KiwiMate-Image-Fast-1.0 KiwiMate-Image-Fast-1.0.safetensors --local-dir models/loras
For image-input workflows (reference images / edits / img2img), load your source picture the same way you would with stock FLUX.2 Klein — the LoRA is name-compatible with the native BFL single-file key layout (double_blocks / single_blocks).
Want to reproduce or tweak the merge itself? merge_lora.py rebuilds the standalone checkpoint from the base + LoRA pair:
pip install numpy
python merge_lora.py \
--base flux-2-klein-9b.safetensors \
--lora KiwiMate-Image-Fast-1.0.safetensors \
--output merged.safetensors
Training details
- Base: black-forest-labs/FLUX.2-klein-9B
- Method: LoRA (rank 32), trained with ai-toolkit
- Final release: step 3000, epoch 2 (
alpha == rank, merged at scale 1.0) - Intermediate snapshots: every 250 steps in
checkpoints/
License
This fine-tune inherits the licensing terms of the base model. Please review FLUX.2-klein-9B's own license terms before commercial use.
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Model tree for KiwiMate/KiwiMate-Image-Fast-1.0
Base model
black-forest-labs/FLUX.2-klein-9B