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jordigonzm/flux_krea_dev
flux_krea_dev is a machine learning model from jordigonzm. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as other.
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Updated Nov 9, 2025
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From the Hugging Face model README
Flux assets for ComfyUI
This repository contains reference weights arranged for ComfyUI under:
models/
diffusion_models/
vae/
text_encoders/
When used with Hugging Face Inference Endpoints, these files are baked into the endpoint image and available at:
/repository/models/...
Configure ComfyUI (extra_model_paths.yaml) to include the paths above.
Important: Check the original model licenses and terms (Black Forest Labs / Comfy-Org / comfyanonymous repos). Some weights do not permit commercial or production use. This repository is provided strictly for demo/testing purposes; you are responsible for ensuring compliance before any other use.
Contents:
models/diffusion_models/ — Flux checkpoint (e.g., flux1-krea-dev_fp8_scaled.safetensors)models/vae/ — VAE (ae.safetensors)models/text_encoders/ — CLIP/T5 encodersIf you need a different layout, adjust extra_model_paths.yaml accordingly.
Hugging Face Inference Endpoints
/.Docker (explicit flags):
docker run --rm --gpus all -p 8080:80 \
-e COMFY_FLAGS="--normalvram --use-pytorch-cross-attention --cache-lru 64 --reserve-vram 1.5" \
your-image:tag
Recommended COMFY_FLAGS
These presets prioritize stability. They’re meant as safe defaults; you should still set COMFY_FLAGS explicitly for your deployment when you know your workload.
--disable-xformers --use-pytorch-cross-attention --cache-lru 2 --reserve-vram 2.0
Minimal recommended hardware