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--- |
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license: other |
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license_name: bespoke-lora-trained-license |
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license_link: https://multimodal.art/civitai-licenses?allowNoCredit=True&allowCommercialUse=Image&allowDerivatives=True&allowDifferentLicense=True |
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tags: |
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- text-to-image |
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- stable-diffusion |
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- lora |
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- diffusers |
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- template:sd-lora |
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- migrated |
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- celebrity |
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base_model: black-forest-labs/FLUX.1-dev |
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instance_prompt: mryan |
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widget: |
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- text: 'photo of a female, having a coffee at a diner, short blonde hair,, smiling, happy,' |
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output: |
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url: >- |
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36676619.jpeg |
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- text: 'color photo, vibrant colours, photo of a female, standing next to a tree, short blond wavy hair, top gun,, smiling, happy,' |
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output: |
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url: >- |
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36676618.jpeg |
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- text: 'color photo, vibrant colours, photo of a female, walking in New York City , short hair,' |
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output: |
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url: >- |
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36676617.jpeg |
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--- |
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# Meg Ryan |
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<Gallery /> |
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([CivitAI](https://civitai.com/models/)) |
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## Model description |
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<p>Defiantly one of my favourites from the 80's and 90's</p><p></p><p>don't forget to follow me for more!!!</p><p>Niko3DX</p> |
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## Trigger words |
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You should use `mryan` to trigger the image generation. |
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## Download model |
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Weights for this model are available in Safetensors format. |
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[Download](/Keltezaa/meg-ryan/tree/main) them in the Files & versions tab. |
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## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers) |
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```py |
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from diffusers import AutoPipelineForText2Image |
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import torch |
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device = "cuda" if torch.cuda.is_available() else "cpu" |
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pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to(device) |
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pipeline.load_lora_weights('Keltezaa/meg-ryan', weight_name='meg-ryan.safetensors') |
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image = pipeline('color photo, vibrant colours, photo of a female, walking in New York City , short hair,').images[0] |
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``` |
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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) |
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