--- license: mit library_name: diffusers pipeline_tag: text-to-image tags: - text-to-image - lens - flux - gpt-oss --- # Lens (base) Self-contained diffusers-layout snapshot of Microsoft's **Lens** text-to-image model, re-assembled for in-house (SceneWorks) use after Microsoft removed the original `microsoft/Lens` repository from the Hub. This is a **repackage**, not a retrain — every weight is byte-identical to a public upstream source (verified by tensor-level comparison against Comfy-Org's authentic redistribution): | Component | Source | License | |------------------|------------------------------------------------------------------------|------------| | `transformer/` | Lens DiT, bf16 — from [`Comfy-Org/Lens`](https://huggingface.co/Comfy-Org/Lens) (`diffusion_models/lens_bf16.safetensors`) | MIT | | `text_encoder/` | gpt-oss-20b (MXFP4), used encoder-only — from [`openai/gpt-oss-20b`](https://huggingface.co/openai/gpt-oss-20b) | Apache-2.0 | | `tokenizer/` | gpt-oss tokenizer — from [`openai/gpt-oss-20b`](https://huggingface.co/openai/gpt-oss-20b) | Apache-2.0 | | `vae/` | FLUX.2 VAE (`AutoencoderKLFlux2`) — from [`black-forest-labs/FLUX.2-dev`](https://huggingface.co/black-forest-labs/FLUX.2-dev) | FLUX.2-dev license | The Lens text encoder is stock, frozen `gpt-oss-20b` (tensor-verified identical to Comfy's `gpt_oss_20b_nvfp4` up to quantization), and the VAE is stock FLUX.2-dev (full-file identical to Comfy's `flux2-vae`). Only the `transformer/` DiT is Lens-specific. ## Layout ``` tokenizer/ tokenizer.json, tokenizer_config.json, special_tokens_map.json text_encoder/ model-0000*-of-00002.safetensors (MXFP4), model.safetensors.index.json, config.json transformer/ lens_bf16.safetensors vae/ diffusion_pytorch_model.safetensors, config.json ``` Sampling defaults for the base model: **20 steps, guidance 5.0**. For the distilled variant see `SceneWorks/Lens-Turbo` (4 steps, guidance 1.0).