I've been researching all over for a tutorial/guide to load a civitAI model (https://civitai.com/models/4823/deliberate) into pytorch and then use it for Inference.
Most research leads to the following:
- Create your base model (which should have the same model Architecture as the model from where the checkpoint was save).
- Then loading the checkpoint using torch.load()
- torch.load_state_dict(loaded_checkpoint)
However, the models on civitai only have the ckpt file and nothing more. So cannot do step 1. I do know it's possible, because the GUI version AUTOMATIC1111 is able to do it.
PS. I do know that the same deliberate model is available on huggingface.co and can be downloaded like standard stable diffusion models, but i'm interested in working with the ckpt file alone and do it the way AUTO1111 does it.
model_id = "stabilityai/stable-diffusion-2-1"
model = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
model.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
# Load the Checkpoint File
ckpt_path = '/Users/XXXX/XXXX/model.ckpt'
checkpoint = torch.load(ckpt_path, map_location="cpu")
model.load_state_dict(checkpoint['state_dict'])
model.eval()
image = model(prompt='xxxxxx')
