Actually use the `lm_path` config option.

hypertrain.py

@@ -270,7 +270,7 @@ gas = train_config["gas"]
 
 Path(train_config["save_path"]).mkdir(parents=True, exist_ok=True)
 
-model = lm_utils.load_from_path("pretrained/sigurdv4").to(gpu).bfloat16()
+model = lm_utils.load_from_path(train_config["lm_path"]).to(gpu).bfloat16()
 for param in model.parameters():
     param.requires_grad = False