fal/flux-2-klein-4B-background-remove-lora

Prompt

Remove the background from the image

Prompt

Remove the background from the image

Prompt

Remove the background from the image

Prompt

Remove the background from the image

✂️ Flux Background Remove LoRA

Remove backgrounds and isolate subjects with AI

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🎯 What does this model do?

This LoRA removes the background from images and isolates the main subject. Simply provide an image, and the model will extract the subject with a clean background removal.

┌─────────────────────────────────────┐
│  ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░  │
│  ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░  │  Background
│  ░░░░░░░░░ [Subject] ░░░░░░░░░░░░░  │  gets removed
│  ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░  │  cleanly
│  ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░  │
└─────────────────────────────────────┘

Perfect for product photography, subject isolation, and creative compositions.

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🖼️ Examples

Input	Output (background removed)

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🚀 Quick Start

Prompt

Remove the background from the image

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💻 Usage

Try it Live on fal.ai

▶️ Open Playground

With fal.ai SDK

import fal_client

def on_queue_update(update):
    if isinstance(update, fal_client.InProgress):
        for log in update.logs:
           print(log["message"])

result = fal_client.subscribe(
    "fal-ai/flux-2/klein/4b/base/edit/lora",
    arguments={
        "prompt": "Remove the background from the image",
        "model_name": None,
        "loras": [{
            "path": "https://huggingface.co/fal/flux-2-klein-4B-background-remove-lora/resolve/main/flux-background-remove-lora.safetensors",
            "scale": 1.1
        }],
        "embeddings": [],
        "image_urls": ["https://your-image.png"]
    },
    with_logs=True,
    on_queue_update=on_queue_update,
)
print(result)

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📦 Model Files

File	Use Case
flux-background-remove-lora.safetensors	fal.ai
sQn8ANj2lbtrfeemXQta0_pytorch_lora_weights_comfy_converted.safetensors	ComfyUI

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🎓 Training Details

Click to expand

Dataset

• Size: 100 image pairs
• Content: Diverse subjects with background removal including:
  • People: portraits, full body shots
  • Products: electronics, furniture, accessories
  • Animals: pets, wildlife
  • Objects: vehicles, art pieces, everyday items
• Output: Clean subject isolation
• Aspect ratios: Various (1:1, 16:9, 9:16, 4:3, 3:4, etc.)

Training

• Base Model: FLUX.2-Klein 4B
• Platform: fal.ai
• Method: LoRA training
• Steps: 4000
• Learning Rate: 0.00005

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🎮 Use Cases

• Product Photography: Isolate products for e-commerce listings
• Portrait Editing: Remove backgrounds from portraits
• Creative Compositing: Extract subjects for new compositions
• Marketing Materials: Create clean cutouts for designs

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⚠️ Limitations

• Works best with clear subject-background separation
• Complex subjects with fine details (hair, fur) may have artifacts at edges
• Semi-transparent objects may not be perfectly isolated

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📄 License

Apache 2.0

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Created by @ilkerzgi • Trained with fal.ai