inference: prefer model.safetensors

inference.py

@@ -164,14 +164,19 @@ class K3VisionEmbedder:
             return cls(repo_or_path, device=device, **kw)
         from huggingface_hub import hf_hub_download
         from huggingface_hub.utils import EntryNotFoundError
-        try:                                               # prefer safetensors
-            path = hf_hub_download(repo_or_path, "k3vit2fe2_proj.safetensors", revision=revision)
+        try:
+            hf_hub_download(repo_or_path, "config.json", revision=revision)   # sibling config
+        except Exception:  # noqa: BLE001
+            pass
+        path = None
+        for name in ("model.safetensors", "k3vit2fe2_proj.safetensors", "k3vit2fe2_proj.pt"):
             try:
-                hf_hub_download(repo_or_path, "config.json", revision=revision)   # sibling config
-            except Exception:  # noqa: BLE001
-                pass
-        except EntryNotFoundError:
-            path = hf_hub_download(repo_or_path, "k3vit2fe2_proj.pt", revision=revision)
+                path = hf_hub_download(repo_or_path, name, revision=revision)
+                break
+            except EntryNotFoundError:
+                continue
+        if path is None:
+            raise FileNotFoundError(f"no projector checkpoint found in {repo_or_path}")
         return cls(path, device=device, **kw)
 
     @torch.no_grad()