End of training
Browse files- README.md +9 -5
- pytorch_lora_weights.safetensors +3 -0
README.md
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# LoRA DreamBooth - herve76/bb
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## MODEL IS CURRENTLY TRAINING ...
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Last checkpoint saved: checkpoint-500
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These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
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The weights were trained on the concept prompt:
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```
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bbhf
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```
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Use this keyword to trigger your custom model in your prompts.
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LoRA for the text encoder was enabled: False.
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Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
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## Usage
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```
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pip install diffusers --upgrade
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```
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In addition make sure to install transformers, safetensors, accelerate as well as the invisible watermark:
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```
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pip install invisible_watermark transformers accelerate safetensors
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```
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To just use the base model, you can run:
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```python
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import torch
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from diffusers import DiffusionPipeline, AutoencoderKL
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vae = AutoencoderKL.from_pretrained('madebyollin/sdxl-vae-fp16-fix', torch_dtype=torch.float16)
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pipe = DiffusionPipeline.from_pretrained(
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"stabilityai/stable-diffusion-xl-base-1.0",
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vae=vae, torch_dtype=torch.float16, variant="fp16",
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use_safetensors=True
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)
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pipe.to("cuda")
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# This is where you load your trained weights
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pipe.load_lora_weights('herve76/bb')
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prompt = "A majestic bbhf jumping from a big stone at night"
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image = pipe(prompt=prompt, num_inference_steps=50).images[0]
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```
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# LoRA DreamBooth - herve76/bb
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These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
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The weights were trained on the concept prompt:
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```
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bbhf
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+
```
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Use this keyword to trigger your custom model in your prompts.
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LoRA for the text encoder was enabled: False.
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Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
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## Usage
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```
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pip install diffusers --upgrade
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```
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+
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In addition make sure to install transformers, safetensors, accelerate as well as the invisible watermark:
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```
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pip install invisible_watermark transformers accelerate safetensors
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```
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+
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To just use the base model, you can run:
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+
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```python
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import torch
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from diffusers import DiffusionPipeline, AutoencoderKL
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vae = AutoencoderKL.from_pretrained('madebyollin/sdxl-vae-fp16-fix', torch_dtype=torch.float16)
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pipe = DiffusionPipeline.from_pretrained(
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"stabilityai/stable-diffusion-xl-base-1.0",
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vae=vae, torch_dtype=torch.float16, variant="fp16",
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use_safetensors=True
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)
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pipe.to("cuda")
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# This is where you load your trained weights
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pipe.load_lora_weights('herve76/bb')
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prompt = "A majestic bbhf jumping from a big stone at night"
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image = pipe(prompt=prompt, num_inference_steps=50).images[0]
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```
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pytorch_lora_weights.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:8e5749fa827cd375227d8b05391b2a6ac765bbd54a4fa83b444ec8869ccec999
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size 23401064
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