diff --git a/stellarphot/notebooks/photometry/06-transit-fit-template.ipynb b/stellarphot/notebooks/photometry/06-transit-fit-template.ipynb
index 7de81868..c5ca34d2 100644
--- a/stellarphot/notebooks/photometry/06-transit-fit-template.ipynb
+++ b/stellarphot/notebooks/photometry/06-transit-fit-template.ipynb
@@ -71,7 +71,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -270,6 +270,7 @@
     "binned = aggregate_downsample(ts, time_bin_size=model_options.bin_size * u.min)\n",
     "binned2 = aggregate_downsample(ts2, time_bin_size=model_options.bin_size * u.min, aggregate_func=add_quad)\n",
     "\n",
+    "binned[\"normalized_flux_error\"] = binned2[\"normalized_flux_error\"]\n",
     "# binned_time = BinnedTimeSeries(photometry['bjd'], time_bin_start=first_time, time_bin_end=last_time, time_bin_size=bin_size)"
    ]
   },
@@ -299,34 +300,15 @@
     "# Make the model\n",
     "mod = TransitModelFit()\n",
     "\n",
-    "# Load data\n",
-    "mod.times = (np.array((binned[\"time_bin_start\"] + binned[\"time_bin_size\"]/2).value) - 2400000)\n",
-    "mod.data = binned[\"normalized_flux\"].value\n",
-    "mod.weights = 1 / (binned2[\"normalized_flux_error\"].value)\n",
-    "mod.airmass = np.array(binned[\"airmass\"])\n",
-    "mod.width = np.array(binned[\"width\"])\n",
-    "mod.spp = np.array(binned[\"sky_per_pix_avg\"])\n",
-    "\n",
     "# Setup the model\n",
     "mod.setup_model(\n",
+    "    binned_data=binned,\n",
     "    t0=mid.jd - 2400000,  # midpoint, BJD\n",
     "    depth=tess_info.depth_ppt,  # parts per thousand\n",
     "    duration=tess_info.duration.to(\"day\").value,  # days\n",
     "    period=tess_info.period.to(\"day\").value,  # days\n",
-    ")\n",
-    "\n",
-    "# Setup the model more 🙄\n",
-    "mod.model.t0.bounds = [\n",
-    "    mid.jd - 2400000 - (model_options.transit_time_range * u.min).to(\"day\").value / 2,\n",
-    "    mid.jd - 2400000 + (model_options.transit_time_range * u.min).to(\"day\").value / 2,\n",
-    "]\n",
-    "mod.model.t0.fixed = model_options.keep_transit_time_fixed\n",
-    "mod.model.a.fixed = model_options.keep_radius_orbit_fixed\n",
-    "mod.model.rp.fixed = model_options.keep_radius_planet_fixed\n",
-    "\n",
-    "mod.model.spp_trend.fixed = not model_options.fit_spp\n",
-    "mod.model.airmass_trend.fixed = not model_options.fit_airmass\n",
-    "mod.model.width_trend.fixed = not model_options.fit_width\n"
+    "    model_options=model_options,\n",
+    ")\n"
    ]
   },
   {
diff --git a/stellarphot/transit_fitting/core.py b/stellarphot/transit_fitting/core.py
index 63a2c576..72d55019 100644
--- a/stellarphot/transit_fitting/core.py
+++ b/stellarphot/transit_fitting/core.py
@@ -1,6 +1,7 @@
 import warnings
 
 import numpy as np
+from astropy import units as u
 from astropy.modeling.fitting import LevMarLSQFitter, _validate_model
 from astropy.modeling.models import custom_model
 from pydantic import BaseModel
@@ -397,6 +398,7 @@ def transit_model_with_trends(
 
     def setup_model(
         self,
+        binned_data=None,
         t0=0,
         depth=0,
         duration=0,
@@ -405,6 +407,7 @@ def setup_model(
         airmass_trend=0.0,
         width_trend=0.0,
         spp_trend=0.0,
+        model_options=None,
     ):
         """
         Configure a transit model for fitting. The ``duration`` and ``depth``
@@ -441,11 +444,28 @@ def setup_model(
         spp_trend : float
             Coefficient for a linear trend in sky per pixel.
 
+        options : TransitModelOptions, optional
+            Options for the transit model fit.
+
         Returns
         -------
         None
             Sets values for the model parameters.
         """
+        if binned_data:
+            self.times = (
+                np.array(
+                    (
+                        binned_data["time_bin_start"] + binned_data["time_bin_size"] / 2
+                    ).value
+                )
+                - 2400000
+            )
+            self.data = binned_data["normalized_flux"].value
+            self.weights = 1 / (binned_data["normalized_flux_error"].value)
+            self.airmass = np.array(binned_data["airmass"])
+            self.width = np.array(binned_data["width"])
+            self.spp = np.array(binned_data["sky_per_pix_avg"])
         self._setup_transit_model()
 
         # rp is related to depth in a straightforward way
@@ -473,6 +493,20 @@ def setup_model(
         except ValueError:
             pass
 
+        if model_options is not None:
+            # Setup the model more 🙄
+            self.model.t0.bounds = [
+                t0 - (model_options.transit_time_range * u.min).to("day").value / 2,
+                t0 + (model_options.transit_time_range * u.min).to("day").value / 2,
+            ]
+            self.model.t0.fixed = model_options.keep_transit_time_fixed
+            self.model.a.fixed = model_options.keep_radius_orbit_fixed
+            self.model.rp.fixed = model_options.keep_radius_planet_fixed
+
+            self.model.spp_trend.fixed = not model_options.fit_spp
+            self.model.airmass_trend.fixed = not model_options.fit_airmass
+            self.model.width_trend.fixed = not model_options.fit_width
+
     def fit(self):
         """
         Perform a fit and update the model with best-fit values.