diff --git a/pippin/classifiers/classifier.py b/pippin/classifiers/classifier.py
index dc96cafa..9dc88a2e 100644
--- a/pippin/classifiers/classifier.py
+++ b/pippin/classifiers/classifier.py
@@ -159,6 +159,8 @@ def get_num_ranseed(sim_tasks, lcfit_tasks):
             name = config["CLASSIFIER"]
             cls = ClassifierFactory.get(name)
             options = config.get("OPTS", {})
+            if options == None:
+                Task.fail_config(f"Classifier {clas_name} has no OPTS specified -- either remove the OPTS keyword or specify some options under it")
             if "MODE" not in config:
                 Task.fail_config(f"Classifier task {clas_name} needs to specify MODE as train or predict")
             mode = config["MODE"].lower()
@@ -169,7 +171,7 @@ def get_num_ranseed(sim_tasks, lcfit_tasks):
                 mode = Classifier.PREDICT
 
             # Prevent mode = predict and SIM_FRACTION < 1
-            if mode == Classifier.PREDICT and "SIM_FRACTION" in options and options["SIM_FRACTION"] < 1:
+            if mode == Classifier.PREDICT and options.get("SIM_FRACTION", 1) > 1:
                 Task.fail_config("SIM_FRACTION must be 1 (all sims included) for predict mode")
 
             # Validate that train is not used on certain classifiers
diff --git a/pippin/classifiers/scone.py b/pippin/classifiers/scone.py
index 770fdbf6..57267086 100644
--- a/pippin/classifiers/scone.py
+++ b/pippin/classifiers/scone.py
@@ -100,7 +100,7 @@ def make_heatmaps_sbatch_header(self):
       header_dict = {
             "REPLACE_LOGFILE": self.heatmaps_log_path,
             "REPLACE_WALLTIME": "12:00:00", #TODO: change to scale with # of heatmaps expected
-            "REPLACE_MEM": "64GB",
+            "REPLACE_MEM": self.options.get("HEATMAPS_MEM", "32GB"),
           }
       heatmaps_sbatch_header = self.make_sbatch_header("HEATMAPS_BATCH_FILE", header_dict)
 
@@ -111,7 +111,7 @@ def make_model_sbatch_script(self):
       header_dict = {
               "REPLACE_NAME": self.job_base_name,
               "REPLACE_LOGFILE": str(Path(self.output_dir) / "output.log"),
-              "REPLACE_MEM": "32GB",
+              "REPLACE_MEM": self.options.get("MODEL_MEM", "64GB"),
               "REPLACE_WALLTIME": "4:00:00" if self.gpu else "12:00:00", # 4h is max for gpu
               }
       model_sbatch_header = self.make_sbatch_header("MODEL_BATCH_FILE", header_dict, use_gpu=self.gpu)
@@ -221,7 +221,7 @@ def _make_config(self, metadata_paths, lcdata_paths, mode, heatmaps_created):
         config["batch_size"] = self.options.get("BATCH_SIZE", 32) # TODO: replace with percentage of total size?
         config["Ia_fraction"] = self.options.get("IA_FRACTION", 0.5)
         config["output_path"] = self.output_dir
-        config["trained_model"] = self.options.get("MODEL", False)
+        config["trained_model"] = self.options.get("MODEL", None)
         config["kcor_file"] = self.options.get("KCOR_FILE", None)
         config["mode"] = mode
         config["job_base_name"] = self.job_base_name