diff --git a/compiler/characterizer/lib.py b/compiler/characterizer/lib.py
index 948f8e47..ad1f5e1c 100644
--- a/compiler/characterizer/lib.py
+++ b/compiler/characterizer/lib.py
@@ -11,9 +11,7 @@ import math
 import datetime
 from .setup_hold import *
 from .delay import *
-from .elmore import *
 from .charutils import *
-from .linear_regression import *
 import tech
 import numpy as np
 from globals import OPTS
@@ -585,16 +583,24 @@ class lib:
     def compute_delay(self):
         """Compute SRAM delays for current corner"""
         if self.use_model:
+            model_name_lc = OPTS.model_name.lower()
+            if model_name_lc == "linear_regression":
+                from .linear_regression import linear_regression as model
+            elif model_name_lc == "elmore":
+                from .elmore import elmore as model
+            else:
+                debug.error("{} model not recognized. See options.py for available models.".format(OPTS.model_name))
             import math
             #FIXME: ML models only designed for delay. Cannot produce all values for Lib
-            d = linear_regression()
-            temp_wpr = 2.0 #OPTS not working right now
+            m = model()
+            #temp_wpr = 2.0 #OPTS not working right now
             log_num_words = math.log(OPTS.num_words, 2)
+            debug.info(1, "OPTS.words_per_row={}".format(OPTS.words_per_row))
             model_inputs = [log_num_words, 
                             OPTS.word_size, 
-                            temp_wpr, 
+                            OPTS.words_per_row, 
                             self.sram.width * self.sram.height]
-            char_results = d.get_prediction(model_inputs)
+            char_results = m.get_prediction(model_inputs)
         
             #self.d = elmore(self.sram, self.sp_file, self.corner)
             # char_results = self.d.analytical_delay(self.slews,self.loads)
diff --git a/compiler/options.py b/compiler/options.py
index e4a61052..f6915035 100644
--- a/compiler/options.py
+++ b/compiler/options.py
@@ -103,7 +103,9 @@ class options(optparse.Values):
     use_pex = False
     # Output config with all options
     output_extended_config = True
-
+    # Determines which analytical model to use.
+    # Available Models: elmore, linear_regression
+    model_name = "linear_regression"
 
     ###################
     # Tool options
@@ -152,8 +154,6 @@ class options(optparse.Values):
     bitcell = "bitcell"
     buf_dec = "pbuf"
     column_mux_array = "column_mux_array"
-    col_cap = "col_cap"
-    col_cap_array = "col_cap_array"
     control_logic = "control_logic"
     decoder = "hierarchical_decoder"
     delay_chain = "delay_chain"
@@ -162,12 +162,10 @@ class options(optparse.Values):
     inv_dec = "pinv"
     nand2_dec = "pnand2"
     nand3_dec = "pnand3"
-    nand4_dec = "pnand4"
+    nand4_dec = "pnand4" # Not available right now
     precharge_array = "precharge_array"
     ptx = "ptx"
     replica_bitline = "replica_bitline"
-    row_cap = "row_cap"
-    row_cap_array = "row_cap_array"
     sense_amp_array = "sense_amp_array"
     sense_amp = "sense_amp"
     tri_gate_array = "tri_gate_array"