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RUM-FLUX.2-klein-4B-ConvRot-Quantized
leafmoone/RUM-FLUX.2-klein-4B-ConvRot-Quantized
RUM-FLUX.2-klein-4B-ConvRot-Quantized is a image-to-image model from leafmoone. Use it when you need one image transformed into another. It is set up for diffusers. The card lists the license as other.
Post-training ConvRot quantizations of RUM-FLUX.2-klein-4B-preview, based on FLUX.2-klein-base-4B. The repository provides a quality-first INT8 model and a smaller hybrid INT4 model. RUM's dual text-conditioning proje…
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.safetensors6.7 GB · 100%
At a glance
- Task
- Image-to-Image
- Library
- diffusers
- License
- other
- Access
- Public
- Created
- Jul 20, 2026
- Updated
- Jul 20, 2026
- SHA
- 2f284cf8
Base models
Model card
From the Hugging Face model README
RUM FLUX.2 Klein 4B ConvRot Quantized
Post-training ConvRot quantizations of RUM-FLUX.2-klein-4B-preview, based on FLUX.2-klein-base-4B. The repository provides a quality-first INT8 model and a smaller hybrid INT4 model. RUM's dual text-conditioning projections and sensitive input, output, normalization, and modulation layers remain in BF16.
Files
rum-flux2-int8-convrot-adaround-realcal-hq.safetensors: INT8 ConvRot + AdaRound with real-activation calibration.rum-flux2-int4-hybrid-convrot-adaround-realcal-hq.safetensors: hybrid INT4 ConvRot + AdaRound with real-activation calibration; incompatible or quality-sensitive layers remain BF16.standalone_inference.py: self-contained RUM architecture and quantized runtime entry point for text-to-image and image editing.
Download the FLUX.2 Klein 4B base model and the SDXL/WAI teacher checkpoint separately, then pass their local paths to standalone_inference.py. Run python standalone_inference.py --help for all options. The recommended defaults are 20 steps for text-to-image and 10 steps for editing.
Comparison
- Task
- Image-to-Image
- Library
- diffusers
- License
- other
- Created
- Jul 20, 2026
- Updated
- Jul 20, 2026