End of training

README.md

@@ -15,19 +15,15 @@ datasets:
     
 # LoRA DreamBooth - herve76/bbhf2
 
-## MODEL IS CURRENTLY TRAINING ...
-Last checkpoint saved: checkpoint-500
-
 These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0. 
 
 The weights were trained on the concept prompt: 
 ```
 bbhf2
-```
+```  
 Use this keyword to trigger your custom model in your prompts. 
 
 LoRA for the text encoder was enabled: False.
-
 Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
 
 ## Usage
@@ -36,24 +32,32 @@ Make sure to upgrade diffusers to >= 0.19.0:
 ```
 pip install diffusers --upgrade
 ```
+
 In addition make sure to install transformers, safetensors, accelerate as well as the invisible watermark:
 ```
 pip install invisible_watermark transformers accelerate safetensors
 ```
+
 To just use the base model, you can run:
+
 ```python
 import torch
 from diffusers import DiffusionPipeline, AutoencoderKL
+
 vae = AutoencoderKL.from_pretrained('madebyollin/sdxl-vae-fp16-fix', torch_dtype=torch.float16)
+
 pipe = DiffusionPipeline.from_pretrained(
     "stabilityai/stable-diffusion-xl-base-1.0",
     vae=vae, torch_dtype=torch.float16, variant="fp16",
     use_safetensors=True
 )
+
 pipe.to("cuda")
+
 # This is where you load your trained weights
 pipe.load_lora_weights('herve76/bbhf2')
 
 prompt = "A majestic bbhf2 jumping from a big stone at night"
+
 image = pipe(prompt=prompt, num_inference_steps=50).images[0]
 ```

pytorch_lora_weights.safetensors

@@ -0,0 +1,3 @@
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+size 23401064