--- license: other license_name: flux-1-dev-non-commercial-license license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md language: - en tags: - flux - diffusers - lora - replicate base_model: "black-forest-labs/FLUX.1-dev" pipeline_tag: text-to-image # widget: # - text: >- # prompt # output: # url: https://... instance_prompt: TOK --- # Gamzekocc_Fluxx Trained on Replicate using: https://replicate.com/ostris/flux-dev-lora-trainer/train ## Trigger words You should use `TOK` to trigger the image generation. ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers) ```py from diffusers import AutoPipelineForText2Image, AutoencoderKL import torch # 1. Ana modeli yükle pipeline = AutoPipelineForText2Image.from_pretrained( "SG161222/Realistic_Vision_V6.0_B1_noVAE", torch_dtype=torch.float16, variant="fp16" ).to("cuda") # 2. VAE ekle (opsiyonel) pipeline.vae = AutoencoderKL.from_pretrained( "stabilityai/sd-vae-ft-mse", torch_dtype=torch.float16 ).to("cuda") # 3. LoRA'yı yükle pipeline.load_lora_weights( "codermert/gamzekocc_fluxx", weight_name="lora.safetensors", adapter_name="fluxx_style" ) # 4. Görüntü oluştur image = pipeline( prompt="portrait of a cyber ninja, , ultra-detailed, 8K", negative_prompt="blurry, cartoon, deformed", num_inference_steps=30 ).images[0] image.save("cyber_ninja.png") ``` For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)