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license: apache-2.0
base_model: black-forest-labs/FLUX.2-klein-4B
tags:
  - lora
  - flux.2
  - flux2-klein
  - object-removal
  - inpainting
  - image-editing
  - image-to-image
  - mirror
library_name: diffusers
pipeline_tag: image-to-image
instance_prompt: Remove the highlighted object from the scene

Flux Object Removal — FLUX.2-klein-4B LoRA (mirror)

A rank-16 edit LoRA for FLUX.2-klein-4B that removes a highlighted object from an image and fills the region with contextually appropriate content (inpainting-style removal).

This is a verbatim mirror, not original work. All credit belongs to the original author, fal (fal.ai). This repository exists so downstream code can depend on a stable, long-lived URL; the file is byte-for-byte identical to the source (verify the SHA-256 below).

Attribution & source

Original author: fal (fal.ai)
Source: https://huggingface.co/fal/flux-2-klein-4B-object-remove-lora
Live demo (author): https://fal.ai/models/fal-ai/flux-2/klein/4b/base/edit/lora
License: Apache-2.0, as published by fal on the source repository. Mirrored here under those terms with attribution retained (see NOTICE). If you are the author and want this mirror changed or removed, open a discussion and it will be actioned promptly.

Provenance (verify the mirror)


File	`flux-object-remove-lora.safetensors`
Size	58,441,728 bytes (~58 MB)
SHA-256	`70CEEA34A8BCD6E7D0249BA26BB59A3CD8B8C38745FAB65A3EB112A5C13E3C69`
Tensors	136 (f32)
Rank	16
Base model	`black-forest-labs/FLUX.2-klein-4B`
Key dialect	BFL-fused with PEFT `base_model.model.` prefix

The source repo also ships a ComfyUI-converted variant (..._comfy_converted.safetensors, diffusion_model. prefix); this mirror carries the canonical diffusers/PEFT file. Both map to the same 40 double + 40 single (80) targets.

Usage

Base: FLUX.2-klein-4B (image edit). Mark/highlight the object to remove in the input.
Prompt: Remove the highlighted object from the scene
Strength (scale): ~1.1 (per the author's fal.ai SDK example).

Disclaimer

Mirrored in good faith based on fal's Apache-2.0 release. No affiliation with or endorsement by fal is implied.