Granddyser/BigLoveKlein-Collection

BigLove Klein Collection

Support Notice

I pay for these models out of my own pocket and share them here so people can access them freely. Please understand that this repository is provided as-is. I’m not able to provide individual support, troubleshooting, custom instructions, or answer repeated questions for every upload.

Feel free to download and use the files, but please don’t expect active maintenance or personal support.

Available Files

File	Format	Size	Use Case
bigLove_klein4_int8_convrot.safetensors	int8	~9 GB	na
bigLoveKlein4_fp8mixed.safetensors	fp8 (pruned)	~9 GB	Pruned weights
bigLove_klein4_bf16.safetensors	BF16 (pruned)	~18 GB	Pruned weights
bigLove_klein3_Q5_K_M.gguf	GGUF	6 GB	v.3
bigLove_klein3.safetensors	BF16	18 GB	v.3
bigLove_klein3_fp8.safetensors	FP8	9 GB	v.3
klein-biglove-v2.1.safetensors	sft	na	na
bigLove_klein2_Bf16.safetensors	BF16	~18 GB	Full precision, best quality
bigLove_klein2_bf16_pruned.safetensors	BF16 (pruned)	~18 GB	Pruned weights, slightly faster
bigLove_klein2_fp8_pruned.safetensors	FP8 (pruned)	~9 GB	Good balance of quality & VRAM
bigLove_klein2_nf4.safetensors	NF4	~5 GB	Low VRAM, fast inference
bigLove_klein2.gguf	GGUF	varies	For GGUF-compatible loaders
bigLove_klein1_fp8.safetensors	FP8	~9 GB	First version, FP8 quantized

Usage

ComfyUI

Place the desired model file in your ComfyUI/models/diffusion_models/ (or unet) folder and select it in the appropriate loader node.

Diffusers

from diffusers import FluxPipeline
import torch

pipe = FluxPipeline.from_pretrained(
    "Granddyser/biglove-klein2-fp8",
    torch_dtype=torch.bfloat16
)
pipe.to("cuda")

image = pipe(
    prompt="your prompt here",
    num_inference_steps=4,
    guidance_scale=0.0,
).images[0]

image.save("output.png")

Acknowledgments

Special thanks to SubtleShader for the motivation.

License

FLUX.2-klein-base-9B is licensed by Black Forest Labs. Inc. under the FLUX.2-klein-base-9B Non-Commercial License. Copyright Black Forest Labs. Inc.