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KiwiMate/KiwiMate-Image-Mini-1.0
KiwiMate-Image-Mini-1.0 is a image-to-image model from KiwiMate. Use it when you need one image transformed into another. It is set up for diffusers. The card lists the license as apache-2.0.
KiwiMate-Image-Mini-1.0 is a LoRA fine-tune of black-forest-labs/FLUX.2-klein-4B, a compact 4B-parameter text-to-image diffusion model. It delivers fast, high-quality image generation while staying lightweight enough…
Downloads · 30 days
507
51% of all-time downloads
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.safetensors8.9 GB · 100%
From the Hugging Face model README
KiwiMate-Image-Mini-1.0 is a LoRA fine-tune of black-forest-labs/FLUX.2-klein-4B, a compact 4B-parameter text-to-image diffusion model. It delivers fast, high-quality image generation while staying lightweight enough to run on consumer GPUs.
| File | Description |
|---|---|
KiwiMate-Image-Mini-1.0.safetensors | Final LoRA weights (92 MB) |
KiwiMate-Image-Mini-1.0_000000250 – _000002750.safetensors | Training step checkpoints |
KiwiMate-Image-Mini-1.0_merged.safetensors | Full merged model (7.75 GB), no base model required |
Load the LoRA on top of the base FLUX.2-klein-4B model:
from diffusers import FluxKleinPipeline
import torch
pipe = FluxKleinPipeline.from_pretrained(
"black-forest-labs/FLUX.2-klein-4B",
torch_dtype=torch.bfloat16,
).to("cuda")
pipe.load_lora_weights("KiwiMate/KiwiMate-Image-Mini-1.0", weight_name="KiwiMate-Image-Mini-1.0.safetensors")
image = pipe("your prompt here").images[0]
For a standalone setup without the base model, use the merged checkpoint:
pipe = FluxKleinPipeline.from_pretrained(
"KiwiMate/KiwiMate-Image-Mini-1.0",
torch_dtype=torch.bfloat16,
).to("cuda")
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Apache 2.0