kimi000/cedar-cloud-83

Version Base v0.1 Seasonal 39-Family, Step 600 EMA

Complete native BF16 diffusers.Flux2KleinPipeline. Trained EMA LoRA weights (rank 32, alpha 64) are merged into the transformer. No FAR or PEFT runtime is needed for inference.

This is the 39-family Version Base v0.1 Seasonal curriculum experiment, not the static AlphaGRPO baseline. Training: 512px, 20 rollout steps, CFG 4, 16 prompts per iteration, group size 14. 100pct denotes a target, not a verified 100% online-authored fraction.

Source run: vb-v01-isolated-lifecycle-20260913. W&B run: fb24f2db64306fd0bf7dc90c08823fa6. Exact experiment, source checkpoint hash, source revision, configuration hash and the complete family list are recorded in provenance.json and export_manifest.json.

verification.json records strict offline reloading, nonzero parameter differences from Base before and after serialization, and same-seed 512px/20-step image differences from Base. These checks validate the export; they are not benchmark results or evidence of quality improvement.

import torch
from diffusers import Flux2KleinPipeline

pipe = Flux2KleinPipeline.from_pretrained(
    "kimi000/cedar-cloud-83", torch_dtype=torch.bfloat16
).to("cuda")
image = pipe(
    prompt="A red ceramic teapot beside two blue cups on a wooden table.",
    height=512, width=512, num_inference_steps=20, guidance_scale=4.0,
    generator=torch.Generator("cuda").manual_seed(0),
).images[0]