metadata
license: mit
library_name: diffusers
pipeline_tag: text-to-image
tags:
- text-to-image
- lens
- flux
- gpt-oss
Lens-Turbo
Self-contained diffusers-layout snapshot of Microsoft's Lens-Turbo (distilled) text-to-image model,
re-assembled for in-house (SceneWorks) use after Microsoft removed the original microsoft/Lens-Turbo
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-Turbo DiT, bf16 — from Comfy-Org/Lens (diffusion_models/lens_turbo_bf16.safetensors) |
MIT |
text_encoder/ |
gpt-oss-20b (MXFP4), used encoder-only — from openai/gpt-oss-20b |
Apache-2.0 |
tokenizer/ |
gpt-oss tokenizer — from openai/gpt-oss-20b |
Apache-2.0 |
vae/ |
FLUX.2 VAE (AutoencoderKLFlux2) — from black-forest-labs/FLUX.2-dev |
FLUX.2-dev license |
The text encoder is stock, frozen gpt-oss-20b and the VAE is stock FLUX.2-dev; only the
transformer/ DiT is Lens-specific. The encoder + VAE are identical to those in SceneWorks/Lens —
only the distilled transformer/ differs.
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_turbo_bf16.safetensors
vae/ diffusion_pytorch_model.safetensors, config.json
Sampling defaults for the distilled model: 4 steps, guidance 1.0 (≈ no CFG).