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- 31654332.jpeg +0 -0
- 31654335.jpeg +0 -0
- 31654340.jpeg +0 -0
- README.md +78 -0
- flux_opus_ascii.safetensors +3 -0
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README.md
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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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- abstract
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- style
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- ai
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base_model: black-forest-labs/FLUX.1-dev
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instance_prompt: opus_ascii
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widget:
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- text: 'ascii art, opus_ascii, will smith eating spaghetti'
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output:
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url: >-
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- text: 'ascii art, opus_ascii, will smith eating spaghetti'
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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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- text: ' '
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output:
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url: >-
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---
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# Opus ASCII FLUX
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<Gallery />
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## Model description
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<p>Trained on Claude Opus 3 ASCII art output latent space discovered by @dyot_meet_mat on twitter </p>
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## Trigger words
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You should use `opus_ascii` 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](/veryVANYA/opus-ascii-flux/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('veryVANYA/opus-ascii-flux', weight_name='flux_opus_ascii.safetensors')
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image = pipeline('`opus_ascii`').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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flux_opus_ascii.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:296da05173ede9e628b60a7d99cd4c0d221bc3c0ef1985b833139aae2a77e51b
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size 89745224
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