--- license: other license_name: flux-non-commercial-license-v2.1 license_link: https://huggingface.co/black-forest-labs/FLUX.2-klein-base-9B/blob/main/LICENSE.md language: - en base_model: - black-forest-labs/FLUX.2-klein-base-9B tags: - text-to-image - scientific-diagrams - methodology-figures - flux - diffusers pipeline_tag: text-to-image --- # SciForma-Base **SciForma-Base** is the Stage 1+2 SFT checkpoint of [SciForma: Structure-Faithful Generation of Scientific Diagrams](https://github.com/microsoft/SciForma), fine-tuned from [FLUX.2-klein-base-9B](https://huggingface.co/black-forest-labs/FLUX.2-klein-base-9B). | Model | Overall ↑ | Comp. ↑ | Arrow ↑ | Text ↑ | |-------|-----------|---------|---------|--------| | SciForma-9B | 69.51 | 74.49 | 66.46 | 67.00 | | **SciForma-Base** | **67.59** | 73.52 | 64.64 | 63.84 | | FLUX.2-klein-base-9B (no fine-tuning) | 33.87 | 42.80 | 25.20 | 23.60 | Scores on SciFormaBench-2K (GPT-5.4 judge, split_dims=True). ## Usage This repository contains only the fine-tuned **transformer** weights. The text encoder, tokenizer, VAE, and scheduler are inherited from the base model. ```python import torch from diffusers import Flux2KleinPipeline, Flux2Transformer2DModel # Load fine-tuned transformer transformer = Flux2Transformer2DModel.from_pretrained( "microsoft/SciForma-Base", subfolder="transformer", torch_dtype=torch.bfloat16, ) # Load full pipeline with base model components pipe = Flux2KleinPipeline.from_pretrained( "black-forest-labs/FLUX.2-klein-base-9B", transformer=transformer, torch_dtype=torch.bfloat16, ) pipe.enable_model_cpu_offload() # Generate prompt = "The figure illustrates a transformer architecture with encoder and decoder..." image = pipe( prompt, height=576, width=1008, num_inference_steps=28, guidance_scale=4.0, ).images[0] image.save("output.png") ``` ## Training Details - **Base model**: FLUX.2-klein-base-9B (9.08B parameters) - **Stage 1**: Full fine-tuning on 661K arXiv methodology diagrams at 768px (200K steps, 8× B200) - **Stage 2**: Joint generation + editing fine-tuning on 244K high-quality 1024px diagrams + 70K editing triplets (120K steps, 8× B200) - **Training data**: [microsoft/SciFormaData-700K](https://huggingface.co/datasets/microsoft/SciFormaData-700K) ## License Released under the [FLUX Non-Commercial License v2.1](https://huggingface.co/black-forest-labs/FLUX.2-klein-base-9B/blob/main/LICENSE.md). Non-commercial research use only. > This FLUX Model is licensed by Black Forest Labs Inc. under the FLUX Non-Commercial License. Copyright Black Forest Labs Inc. This model has been modified by Microsoft Research Asia.