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README.md
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license: creativeml-openrail-m
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base_model: runwayml/stable-diffusion-v1-5
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tags:
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- stable-diffusion
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- stable-diffusion-diffusers
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- lora
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inference: true
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# LoRA text2image fine-tuning - juliensimon/stable-diffusion-v1-5-pokemon-lora
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These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were fine-tuned on the lambdalabs/pokemon-blip-captions dataset. You can find some example images in the following.
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---
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license: creativeml-openrail-m
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base_model: runwayml/stable-diffusion-v1-5
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datasets:
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- lambdalabs/pokemon-blip-captions
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tags:
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- stable-diffusion
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- stable-diffusion-diffusers
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- lora
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inference: true
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This model was fine-tuned using 4-bit QLoRa, following the instructions in https://huggingface.co/blog/lora.
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I used a Amazon EC2 g4dn.xlarge instance (1xT4 GPU), with the Deep Learning AMI for PyTorch. Training time was about 6 hours. On-demand price is about $3, which can easily be reduced to about $1 with EC2 Spot Instances.
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# LoRA text2image fine-tuning - juliensimon/stable-diffusion-v1-5-pokemon-lora
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These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were fine-tuned on the lambdalabs/pokemon-blip-captions dataset. You can find some example images in the following.
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