Update weights to be from same repo

cool_models.py

@@ -13,9 +13,6 @@ STEPS = 100
 USE_DDPM = False
 USE_DDIM = False
 USE_CPU = False
-BERT_PATH = "./weights/bert.pt"
-KL_PATH = "./weights/kl-f8.pt"
-INPAINT_PATH = "./weights/inpaint.pt"
 CLIP_SEG_PATH = './weights/rd64-uni.pth'
 CLIP_GUIDANCE = False
 
@@ -79,10 +76,7 @@ def make_models():
 
 
     model, diffusion = create_model_and_diffusion(**model_config)
-
-    # model.from_pretrained("alvanlii/rdm_inpaint")
     model.load_state_dict(model_state_dict, strict=False)
-    # model.save_pretrained("./weights/hf_inpaint")
 
     model.requires_grad_(CLIP_GUIDANCE).eval().to(device)
 
@@ -97,10 +91,7 @@ def make_models():
 
 
     lpips_model = lpips.LPIPS(net="vgg").to(device)
-    hf_kl_path = hf_hub_download("alvanlii/rdm_kl", "kl-f8.pt")
-
-    # kl_model_url = hf_hub_url("alvanlii/rdm_kl", "kl-f8.pt")
-    # kl_cache_path = cached_download(kl_model_url, cache_dir=".")
+    hf_kl_path = hf_hub_download("alvanlii/rdm_inpaint", "kl-f8.pt")
 
     ldm = torch.load(hf_kl_path, map_location="cpu")
     
@@ -111,7 +102,7 @@ def make_models():
     set_requires_grad(ldm, CLIP_GUIDANCE)
 
     bert = BERTEmbedder(1280, 32)
-    hf_bert_path = hf_hub_download("alvanlii/rdm_bert", 'bert.pt')
+    hf_bert_path = hf_hub_download("alvanlii/rdm_inpaint", 'bert.pt')
     # bert = BERTEmbedder.from_pretrained("alvanlii/rdm_bert")
     sd = torch.load(hf_bert_path, map_location="cpu")
     bert.load_state_dict(sd)