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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=False&allowCommercialUse=RentCivit&allowDerivatives=False&allowDifferentLicense=False
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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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+ - concept
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+ - studio
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+ - recording
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+ - gold teeth
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+ - rapping
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+
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+ base_model: runwayml/stable-diffusion-v1-5
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+ instance_prompt: recstudio
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+ widget:
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+ - text: ' '
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+ output:
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+ url: >-
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+ - text: ' '
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+ output:
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+ - text: ' '
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+ output:
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+ url: >-
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+ - text: ' '
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+ output:
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+ url: >-
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+ 24382058.jpeg
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+
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+ ---
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+
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+ # Recording studio
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+
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+ <Gallery />
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+ ## Model description
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+
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+ <p>trained on around 17 images from midjourney of characters in studio.</p><p> This is meant to re-create the concept of recording in Studio. </p><p></p><p>In the training data, there was a lot of emphasis on smoky rooms, gold chains, gold teeth, etc. so you may want to implement those in your promise. It could be a bit heavy handed so I don't know if I would have the weighting set to high try at a lower value around 6 first and work your way up.</p>
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+
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+ ## Trigger words
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+ You should use ` recstudio`, `evang` to trigger the image generation.
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+
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+
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+ ## Download model
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+
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+ Weights for this model are available in Safetensors format.
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+
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+ [Download](/brushpenbob/recording-studio/tree/main) them in the Files & versions tab.
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+
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+ ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
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+
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+ ```py
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+ from diffusers import AutoPipelineForText2Image
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+ import torch
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+
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+ pipeline = AutoPipelineForText2Image.from_pretrained('runwayml/stable-diffusion-v1-5', torch_dtype=torch.float16).to('cuda')
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+ pipeline.load_lora_weights('brushpenbob/recording-studio', weight_name='Recording_studio.safetensors')
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+ image = pipeline('` recstudio`, `evang`').images[0]
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+ ```
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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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