FLUX.2 Klein 4B Step-500 EMA Diffusers Export
This repository contains a complete native Hugging Face Diffusers export of a trained FLUX.2 Klein Base 4B checkpoint. The public repository name is intentionally neutral; full experiment provenance is recorded below for reproducibility.
Provenance
- Source experiment:
flux2_klein_base_4b_diffusionnft_dvreward_prompt_rubric_v4_3_geneval_composition_16prompts_group14_7train_1dvreward_tp1_2node_512px_20step_cfg4_nrt - Experiment variant: prompt-rubric v4.3, GenEval composition-only
- Formal run:
flux2-v43-geneval-formal-0903f430-r2 - Source run code revision:
0903f430244d330b7c18bdba2f9560491b1a6898 - Source checkpoint:
models/step_500.pt - Global step:
500 - Exported weights: EMA
- Source checkpoint SHA-256:
8fa1aef3c311f422f407eb0b06b956581da86cc877a76d3e372c3e6ee608c1b1 - Base model:
black-forest-labs/FLUX.2-klein-base-4B - Base revision:
a3b4f4849157f664bdbc776fd7453c2783562f4d - Training profile: 16 prompts, group size 14, 512 px, 20 rollout steps, CFG 4, 7 policy ranks and 1 DVReward replica per node across 2 nodes
- LoRA rank / alpha:
32 / 64
The EMA LoRA weights were merged into the native BF16 FLUX.2 transformer. The export contains 169 transformer tensors and 3,875,544,576 transformer parameters. DiffusionNFT old-policy training-state tensors were excluded from the inference artifact.
Format
- Pipeline:
diffusers.Flux2KleinPipeline - Transformer:
diffusers.Flux2Transformer2DModel - Precision: BF16
- Scheduler: 1,000 training timesteps, dynamic shifting enabled, deterministic sampling
- Transformer weights: 9 shards
- Text encoder weights: 9 shards
- Maximum shard size: below 1 GB
Verification
The export was strictly reloaded offline with stock Diffusers and generated a 512 x 512 smoke image using 4 inference steps, CFG 4, and seed 0. The merged transformer differs from Base in 60 tensors and 2,422,759,106 elements, with L2 delta 28.82849469865312 and maximum absolute delta 0.008819580078125.
A same-seed Base render was also generated:
- Changed channel values:
730,266 - Mean absolute channel delta:
28.308038075764973 - Maximum absolute channel delta:
249
These checks verify that the exported transformer contains the trained Step-500 EMA weights rather than an unchanged Base transformer. verification.json, smoke images, the export manifest, and SHA-256 checksums are included.
Loading
import torch
from diffusers import Flux2KleinPipeline
pipe = Flux2KleinPipeline.from_pretrained(
"kimi000/copper-reef-47",
torch_dtype=torch.bfloat16,
)
pipe.enable_model_cpu_offload()
image = pipe(
prompt="A red cube beside a blue glass sphere.",
height=1024,
width=1024,
guidance_scale=4.0,
num_inference_steps=20,
).images[0]
See export_manifest.json and verification.json for machine-readable export details.