Update README.md

Add instructions for running the v1.5 variant.

README.md

@@ -105,7 +105,7 @@ python ./train_laion_face_sd15.py
 We have provided `gradio_face2image.py`.  Update the following two lines to point them to your trained model.
 
 ```
-model = create_model('./models/cldm_v21.yaml').cpu()  # If you fine-tuned on SD2.1 base, this does not need to change.
+model = create_model('./models/cldm_v21.yaml').cpu()  # If you fine-tune on SD2.1 base, this does not need to change.
 model.load_state_dict(load_state_dict('./models/control_sd21_openpose.pth', location='cuda'))
 ```
 
@@ -116,7 +116,9 @@ The model has some limitations: while it is empirically better at tracking gaze
 It is recommended to use the checkpoint with [Stable Diffusion 2.1 - Base](stabilityai/stable-diffusion-2-1-base) as the checkpoint has been trained on it.
 Experimentally, the checkpoint can be used with other diffusion models such as dreamboothed stable diffusion.
 
-1. Let's install `diffusers` and related packages:
+To use with Stable Diffusion 1.5, insert `subfolder="diffusion_sd15"` into the from_pretrained arguments.  A v1.5 half-precision variant is provided but untested.
+
+1. Install `diffusers` and related packages:
 ```
 $ pip install diffusers transformers accelerate
 ```
@@ -133,10 +135,16 @@ image = load_image(
     "https://huggingface.co/CrucibleAI/ControlNetMediaPipeFace/resolve/main/samples_laion_face_dataset/family_annotation.png"
 )
 
+# Stable Diffusion 2.1-base:
 controlnet = ControlNetModel.from_pretrained("CrucibleAI/ControlNetMediaPipeFace", torch_dtype=torch.float16, variant="fp16")
 pipe = StableDiffusionControlNetPipeline.from_pretrained(
 	"stabilityai/stable-diffusion-2-1-base", controlnet=controlnet, safety_checker=None, torch_dtype=torch.float16
 )
+# OR
+# Stable Diffusion 1.5:
+controlnet = ControlNetModel.from_pretrained("CrucibleAI/ControlNetMediaPipeFace", subfolder="diffusion_sd15")
+pipe = StableDiffusionControlNetPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", controlnet=controlnet, safety_checker=None)
+
 pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
 
 # Remove if you do not have xformers installed