diff --git a/notebooks/1_VAE_molecular.ipynb b/notebooks/1_VAE_molecular.ipynb
index d53f37d..b2b80b6 100644
--- a/notebooks/1_VAE_molecular.ipynb
+++ b/notebooks/1_VAE_molecular.ipynb
@@ -57,6 +57,7 @@
     "    run_cmd('mv {}/* . '.format(GIT_NAME))\n",
     "    run_cmd('rm -rf {}'.format(GIT_NAME))\n",
     "    run_cmd('pip install --upgrade --force-reinstall tf-nightly-gpu-2.0-preview')\n",
+    "    run_cmd('pip install --upgrade --force-reinstall tensorflow_probability==0.8.0rc0')\n",
     "else:\n",
     "    SRC_DIR='..'\n",
     "    \n",
@@ -392,8 +393,8 @@
    "source": [
     "z = encoder.predict(x_test)\n",
     "recon_x = decoder.predict(z)\n",
-    "print(np.abs(recon_x[0]-x[0]))\n",
-    "print(np.linalg.norm(recon_x[0]-x[0]))"
+    "print(np.abs(recon_x[0]-x_test[0]))\n",
+    "print(np.linalg.norm(recon_x[0]-x_test[0]))"
    ]
   },
   {
@@ -542,10 +543,10 @@
     "\n",
     "## Que esta pasando?\n",
     "\n",
-    "* Iteratar sobre los datos en epochs\n",
-    "* En cada epoch, encodificamos, calculamos la media y log-varianza del posterior aproxiamdor $q(z|x)$\n",
+    "* Iterar sobre los datos en epochs\n",
+    "* En cada epoch, encodificamos, calculamos la media y log-varianza del posterior aproximador $q(z|x)$\n",
     "* Usamos el truco de reparametrizacion para samplear de $q(z|x)$\n",
-    "* Nuestros samples reparametrizados se pasan al decoder para obtain logits de la distribucion generativa $p(x|z)$\n",
+    "* Nuestros samples reparametrizados se pasan al decoder para obtener logits de la distribucion generativa $p(x|z)$\n",
     "\n",
     "#### Funcion de perdida\n",
     "\n",