--- license: other license_name: bespoke-lora-trained-license license_link: https://multimodal.art/civitai-licenses?allowNoCredit=True&allowCommercialUse=1&allowDerivatives=True&allowDifferentLicense=False tags: - text-to-image - stable-diffusion - lora - diffusers - template:sd-lora - migrated - style - woman - man - hair - haircut - hairstyle - styles - hairs base_model: black-forest-labs/FLUX.1-dev instance_prompt: oxwn_crazy_hair widget: - text: ' ' output: url: >- 26476785.jpeg - text: ' ' output: url: >- 26476797.jpeg - text: ' ' output: url: >- 26476844.jpeg - text: ' ' output: url: >- 26476890.jpeg - text: ' ' output: url: >- 26476946.jpeg - text: ' ' output: url: >- 26476982.jpeg - text: ' ' output: url: >- 26476999.jpeg - text: ' ' output: url: >- 26477045.jpeg - text: ' ' output: url: >- 26477133.jpeg - text: ' ' output: url: >- 26477211.jpeg - text: ' ' output: url: >- 26477214.jpeg --- # CRAZY HAIR ## Model description

Here is a LoRA model that I primarily designed to achieve very expressive and voluminous hair, which works well both on photorealistic images and toon-style characters.

Training: 2000 steps

Trigger: oxwn_crazy_hair

Enjoy !

## Trigger words You should use `oxwn_crazy_hair` to trigger the image generation. ## Download model Weights for this model are available in Safetensors format. [Download](/Keltezaa/crazy-hair/tree/main) them in the Files & versions tab. ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers) ```py from diffusers import AutoPipelineForText2Image import torch device = "cuda" if torch.cuda.is_available() else "cpu" pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to(device) pipeline.load_lora_weights('Keltezaa/crazy-hair', weight_name='oxwn_crazy_hair_000002000.safetensors') image = pipeline('`oxwn_crazy_hair`').images[0] ``` 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)