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kimi000/quiet-forest-34
quiet-forest-34 is a text-to-image model from kimi000. Use it when you need an image from a text prompt. It is set up for diffusers. The card lists the license as other.
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…
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From the Hugging Face model README
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.
flux2_klein_base_4b_diffusionnft_dvreward_prompt_rubric_v4_3_1_geneval_16prompts_group14_7train_1dvreward_tp1_2node_512px_20step_cfg4_nrtflux2-v431-geneval-formal-505-142eef2e-a12142eef2e8ea30d30eaff17e3ddb2547f908fc3ccmodels/step_500.pt5002f69fbd3bddee06964755babb25b30b90dfc59c944eef01d6480f40966fa0e25black-forest-labs/FLUX.2-klein-base-4Ba3b4f4849157f664bdbc776fd7453c2783562f4d32 / 64The 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.
diffusers.Flux2KleinPipelinediffusers.Flux2Transformer2DModelThe 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 2,421,531,792 elements, with L2 delta 28.540123379650495 and maximum absolute delta 0.009033203125.
A same-seed Base render was also generated:
762,31136.23766326904297254These 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.
import torch
from diffusers import Flux2KleinPipeline
pipe = Flux2KleinPipeline.from_pretrained(
"kimi000/quiet-forest-34",
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.