From fe99d3fe5dd9fb91c9774e7fdfe95147c10aa9bb Mon Sep 17 00:00:00 2001 From: CalamitousFelicitousness Date: Fri, 16 Jan 2026 01:16:06 +0000 Subject: [PATCH] feat: add FLUX.2 Klein model support Add support for FLUX.2 Klein distilled models (4B and 9B variants): - Add pipeline loader for Flux2KleinPipeline - Add model detection for 'flux.2' + 'klein' patterns - Add pipeline mapping in shared_items - Add shared Qwen3ForCausalLM text encoder handling: - 4B variants use Z-Image-Turbo's Qwen3-8B - 9B variants use FLUX.2-klein-9B's Qwen3-14B - Add reference entries for distilled (4B, 9B) and base models - Update diffusers commit for Flux2KleinPipeline support --- html/reference-distilled.json | 20 ++++++++++++++++ html/reference.json | 18 +++++++++++++++ installer.py | 2 +- modules/sd_detect.py | 2 ++ modules/sd_models.py | 4 ++++ modules/shared_items.py | 2 ++ pipelines/generic.py | 17 ++++++++++++++ pipelines/model_flux2_klein.py | 42 ++++++++++++++++++++++++++++++++++ 8 files changed, 106 insertions(+), 1 deletion(-) create mode 100644 pipelines/model_flux2_klein.py diff --git a/html/reference-distilled.json b/html/reference-distilled.json index d31e3fdc5..36e583ec2 100644 --- a/html/reference-distilled.json +++ b/html/reference-distilled.json @@ -161,5 +161,25 @@ "preview": "Tencent-Hunyuan--HunyuanDiT-v1.1-Diffusers-Distilled.jpg", "tags": "distilled", "extras": "sampler: Default, cfg_scale: 2.0" + }, + "Black Forest Labs FLUX.2 Klein 4B": { + "path": "black-forest-labs/FLUX.2-klein-4B", + "preview": "black-forest-labs--FLUX.2-klein-4B.jpg", + "desc": "FLUX.2-klein-4B is a 4 billion parameter size-distilled version of FLUX.2-dev optimized for consumer GPUs. Achieves sub-second inference with 4 steps while fitting in ~13GB VRAM. Supports both text-to-image generation and multi-reference image editing. Apache 2.0 licensed.", + "skip": true, + "tags": "distilled", + "extras": "sampler: Default, cfg_scale: 4.0, steps: 4", + "size": 8.5, + "date": "2025 January" + }, + "Black Forest Labs FLUX.2 Klein 9B": { + "path": "black-forest-labs/FLUX.2-klein-9B", + "preview": "black-forest-labs--FLUX.2-klein-9B.jpg", + "desc": "FLUX.2-klein-9B is a 9 billion parameter size-distilled version of FLUX.2-dev. Higher quality than 4B variant with sub-second inference using 4 steps. Requires ~29GB VRAM. Supports text-to-image and multi-reference editing. Non-commercial license.", + "skip": true, + "tags": "distilled", + "extras": "sampler: Default, cfg_scale: 4.0, steps: 4", + "size": 18.5, + "date": "2025 January" } } \ No newline at end of file diff --git a/html/reference.json b/html/reference.json index d86214467..63cd80124 100644 --- a/html/reference.json +++ b/html/reference.json @@ -124,6 +124,24 @@ "size": 104.74, "date": "2025 November" }, + "Black Forest Labs FLUX.2 Klein Base 4B": { + "path": "black-forest-labs/FLUX.2-klein-base-4B", + "preview": "black-forest-labs--FLUX.2-klein-base-4B.jpg", + "desc": "FLUX.2-klein-base-4B is the undistilled 4 billion parameter base model of FLUX.2-klein. Requires 50 inference steps for full quality but offers flexibility for fine-tuning. Fits in ~13GB VRAM. Supports text-to-image and multi-reference editing. Apache 2.0 licensed.", + "skip": true, + "extras": "sampler: Default, cfg_scale: 4.0, steps: 50", + "size": 8.5, + "date": "2025 January" + }, + "Black Forest Labs FLUX.2 Klein Base 9B": { + "path": "black-forest-labs/FLUX.2-klein-base-9B", + "preview": "black-forest-labs--FLUX.2-klein-base-9B.jpg", + "desc": "FLUX.2-klein-base-9B is the undistilled 9 billion parameter base model of FLUX.2-klein. Requires 50 inference steps for full quality but offers flexibility for fine-tuning. Requires ~29GB VRAM. Supports text-to-image and multi-reference editing. Non-commercial license.", + "skip": true, + "extras": "sampler: Default, cfg_scale: 4.0, steps: 50", + "size": 18.5, + "date": "2025 January" + }, "Z-Image-Turbo": { "path": "Tongyi-MAI/Z-Image-Turbo", diff --git a/installer.py b/installer.py index 913c7d357..08a4bc3e0 100644 --- a/installer.py +++ b/installer.py @@ -648,7 +648,7 @@ def check_diffusers(): t_start = time.time() if args.skip_all: return - sha = '5efb81fa711863fdece9136ad10788440e658b40' # diffusers commit hash + sha = '61f175660a8ac54f1470a74a810e6c38fb4795d5' # diffusers commit hash # if args.use_rocm or args.use_zluda or args.use_directml: # sha = '043ab2520f6a19fce78e6e060a68dbc947edb9f9' # lock diffusers versions for now pkg = pkg_resources.working_set.by_key.get('diffusers', None) diff --git a/modules/sd_detect.py b/modules/sd_detect.py index 0e93b6d20..a1cb6e913 100644 --- a/modules/sd_detect.py +++ b/modules/sd_detect.py @@ -92,6 +92,8 @@ def guess_by_name(fn, current_guess): new_guess = 'HiDream' elif 'chroma' in fn.lower() and 'xl' not in fn.lower(): new_guess = 'Chroma' + elif 'flux.2' in fn.lower() and 'klein' in fn.lower(): + new_guess = 'FLUX2 Klein' elif 'flux.2' in fn.lower(): new_guess = 'FLUX2' elif 'flux' in fn.lower() or 'flex.1' in fn.lower(): diff --git a/modules/sd_models.py b/modules/sd_models.py index f0a832dd6..8db759e87 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -359,6 +359,10 @@ def load_diffuser_force(detected_model_type, checkpoint_info, diffusers_load_con from pipelines.model_flux2 import load_flux2 sd_model = load_flux2(checkpoint_info, diffusers_load_config) allow_post_quant = False + elif model_type in ['FLUX2 Klein']: + from pipelines.model_flux2_klein import load_flux2_klein + sd_model = load_flux2_klein(checkpoint_info, diffusers_load_config) + allow_post_quant = False elif model_type in ['FLEX']: from pipelines.model_flex import load_flex sd_model = load_flex(checkpoint_info, diffusers_load_config) diff --git a/modules/shared_items.py b/modules/shared_items.py index b5df05390..3186b3d12 100644 --- a/modules/shared_items.py +++ b/modules/shared_items.py @@ -48,6 +48,8 @@ pipelines = { 'Qwen': getattr(diffusers, 'QwenImagePipeline', None), 'HunyuanImage': getattr(diffusers, 'HunyuanImagePipeline', None), 'Z-Image': getattr(diffusers, 'ZImagePipeline', None), + 'FLUX2': getattr(diffusers, 'Flux2Pipeline', None), + 'FLUX2 Klein': getattr(diffusers, 'Flux2KleinPipeline', None), 'LongCat': getattr(diffusers, 'LongCatImagePipeline', None), 'GLM-Image': getattr(diffusers, 'GlmImagePipeline', None), # dynamically imported and redefined later diff --git a/pipelines/generic.py b/pipelines/generic.py index d6dad46c8..0a51c1cec 100644 --- a/pipelines/generic.py +++ b/pipelines/generic.py @@ -200,6 +200,23 @@ def load_text_encoder(repo_id, cls_name, load_config=None, subfolder="text_encod **load_args, **quant_args, ) + # Qwen3ForCausalLM - shared text encoders by hidden_size: + # - Z-Image, Klein-4B: Qwen3-4B (hidden_size=2560) + # - Klein-9B: Qwen3-8B (hidden_size=4096) + elif cls_name == transformers.Qwen3ForCausalLM and allow_shared and shared.opts.te_shared_t5: + if '-9b' in repo_id.lower(): + shared_repo = 'black-forest-labs/FLUX.2-klein-9B' # 9B variants use Qwen3-8B + else: + shared_repo = 'Tongyi-MAI/Z-Image-Turbo' # 4B variants and Z-Image use Qwen3-4B + subfolder = 'text_encoder' + shared.log.debug(f'Load model: text_encoder="{shared_repo}" cls={cls_name.__name__} quant="{quant_type}" loader={_loader("transformers")} shared={shared.opts.te_shared_t5}') + text_encoder = cls_name.from_pretrained( + shared_repo, + cache_dir=shared.opts.hfcache_dir, + subfolder=subfolder, + **load_args, + **quant_args, + ) # load from repo if text_encoder is None: diff --git a/pipelines/model_flux2_klein.py b/pipelines/model_flux2_klein.py new file mode 100644 index 000000000..9b8b05ac8 --- /dev/null +++ b/pipelines/model_flux2_klein.py @@ -0,0 +1,42 @@ +import transformers +import diffusers +from modules import shared, devices, sd_models, model_quant, sd_hijack_te, sd_hijack_vae +from pipelines import generic + + +def load_flux2_klein(checkpoint_info, diffusers_load_config=None): + if diffusers_load_config is None: + diffusers_load_config = {} + repo_id = sd_models.path_to_repo(checkpoint_info) + sd_models.hf_auth_check(checkpoint_info) + + load_args, _quant_args = model_quant.get_dit_args(diffusers_load_config, allow_quant=False) + shared.log.debug(f'Load model: type=Flux2Klein repo="{repo_id}" config={diffusers_load_config} offload={shared.opts.diffusers_offload_mode} dtype={devices.dtype} args={load_args}') + + # Load transformer - Klein uses Flux2Transformer2DModel (same class as Flux2, different size) + transformer = generic.load_transformer(repo_id, cls_name=diffusers.Flux2Transformer2DModel, load_config=diffusers_load_config) + + # Load text encoder - Klein uses Qwen3ForCausalLM (8B), shared across all Klein variants + text_encoder = generic.load_text_encoder(repo_id, cls_name=transformers.Qwen3ForCausalLM, load_config=diffusers_load_config) + + pipe = diffusers.Flux2KleinPipeline.from_pretrained( + repo_id, + transformer=transformer, + text_encoder=text_encoder, + cache_dir=shared.opts.diffusers_dir, + **load_args, + ) + pipe.task_args = { + 'output_type': 'np', + } + diffusers.pipelines.auto_pipeline.AUTO_TEXT2IMAGE_PIPELINES_MAPPING["flux2klein"] = diffusers.Flux2KleinPipeline + diffusers.pipelines.auto_pipeline.AUTO_IMAGE2IMAGE_PIPELINES_MAPPING["flux2klein"] = diffusers.Flux2KleinPipeline + diffusers.pipelines.auto_pipeline.AUTO_INPAINT_PIPELINES_MAPPING["flux2klein"] = diffusers.Flux2KleinPipeline + + del text_encoder + del transformer + sd_hijack_te.init_hijack(pipe) + sd_hijack_vae.init_hijack(pipe) + + devices.torch_gc(force=True, reason='load') + return pipe