diff --git a/ESMFold.ipynb b/ESMFold.ipynb
index 65e9100f..74c15533 100644
--- a/ESMFold.ipynb
+++ b/ESMFold.ipynb
@@ -59,30 +59,33 @@
         "%%time\n",
         "#@title install\n",
         "#@markdown install ESMFold, OpenFold and download Params (~2min 30s)\n",
-        "\n",
+        "version = \"1\" # @param [\"0\", \"1\"]\n",
+        "model_name = \"esmfold_v0.model\" if version == \"0\" else \"esmfold_v0.model\"\n",
         "import os, time\n",
-        "if not os.path.isfile(\"esmfold.model\"):\n",
+        "if not os.path.isfile(model_name):\n",
         "  # download esmfold params\n",
         "  os.system(\"apt-get install aria2 -qq\")\n",
-        "  os.system(\"aria2c -q -x 16 https://colabfold.steineggerlab.workers.dev/esm/esmfold.model &\")\n",
+        "  os.system(f\"aria2c -q -x 16 https://colabfold.steineggerlab.workers.dev/esm/{model_name} &\")\n",
         "\n",
-        "  # install libs\n",
-        "  os.system(\"pip install -q omegaconf pytorch_lightning biopython ml_collections einops py3Dmol\")\n",
-        "  os.system(\"pip install -q git+https://github.com/NVIDIA/dllogger.git\")\n",
+        "  if not os.path.isfile(\"finished_install\"):\n",
+        "    # install libs\n",
+        "    os.system(\"pip install -q omegaconf pytorch_lightning biopython ml_collections einops py3Dmol\")\n",
+        "    os.system(\"pip install -q git+https://github.com/NVIDIA/dllogger.git\")\n",
         "\n",
-        "  # install openfold\n",
-        "  commit = \"6908936b68ae89f67755240e2f588c09ec31d4c8\"\n",
-        "  os.system(f\"pip install -q git+https://github.com/aqlaboratory/openfold.git@{commit}\")\n",
+        "    # install openfold\n",
+        "    commit = \"6908936b68ae89f67755240e2f588c09ec31d4c8\"\n",
+        "    os.system(f\"pip install -q git+https://github.com/aqlaboratory/openfold.git@{commit}\")\n",
         "\n",
-        "  # install esmfold\n",
-        "  os.system(f\"pip install -q git+https://github.com/sokrypton/esm.git\")\n",
+        "    # install esmfold\n",
+        "    os.system(f\"pip install -q git+https://github.com/sokrypton/esm.git\")\n",
+        "    os.system(\"touch finished_install\")\n",
         "\n",
         "  # wait for Params to finish downloading...\n",
-        "  if not os.path.isfile(\"esmfold.model\"):\n",
-        "    # backup source!\n",
-        "    os.system(\"aria2c -q -x 16 https://files.ipd.uw.edu/pub/esmfold/esmfold.model\")\n",
+        "  if not os.path.isfile(model_name):\n",
+        "    print(\"ERROR: downloading esmfold params\")\n",
         "  else:\n",
-        "    while os.path.isfile(\"esmfold.model.aria2\"):\n",
+        "    print(\"waiting for param download...\")\n",
+        "    while os.path.isfile(f\"{model_name}.aria2\"):\n",
         "      time.sleep(5)"
       ]
     },
@@ -94,14 +97,16 @@
         "from string import ascii_uppercase, ascii_lowercase\n",
         "import hashlib, re, os\n",
         "import numpy as np\n",
+        "import torch\n",
         "from jax.tree_util import tree_map\n",
         "import matplotlib.pyplot as plt\n",
         "from scipy.special import softmax\n",
+        "import gc\n",
         "\n",
         "def parse_output(output):\n",
         "  pae = (output[\"aligned_confidence_probs\"][0] * np.arange(64)).mean(-1) * 31\n",
         "  plddt = output[\"plddt\"][0,:,1]\n",
-        "  \n",
+        "\n",
         "  bins = np.append(0,np.linspace(2.3125,21.6875,63))\n",
         "  sm_contacts = softmax(output[\"distogram_logits\"],-1)[0]\n",
         "  sm_contacts = sm_contacts[...,bins<8].sum(-1)\n",
@@ -128,7 +133,7 @@
         "if copies == \"\" or copies <= 0: copies = 1\n",
         "sequence = \":\".join([sequence] * copies)\n",
         "num_recycles = 3 #@param [\"0\", \"1\", \"2\", \"3\", \"6\", \"12\", \"24\"] {type:\"raw\"}\n",
-        "chain_linker = 25 \n",
+        "chain_linker = 25\n",
         "\n",
         "ID = jobname+\"_\"+get_hash(sequence)[:5]\n",
         "seqs = sequence.split(\":\")\n",
@@ -141,10 +146,17 @@
         "elif len(u_seqs) == 1: mode = \"homo\"\n",
         "else: mode = \"hetero\"\n",
         "\n",
-        "if \"model\" not in dir():\n",
-        "  import torch\n",
-        "  model = torch.load(\"esmfold.model\")\n",
+        "if \"model\" not in dir() or model_name != model_name_:\n",
+        "  if \"model\" in dir():\n",
+        "    # delete old model from memory\n",
+        "    del model\n",
+        "    gc.collect()\n",
+        "    if torch.cuda.is_available():\n",
+        "      torch.cuda.empty_cache()\n",
+        "\n",
+        "  model = torch.load(model_name)\n",
         "  model.eval().cuda().requires_grad_(False)\n",
+        "  model_name_ = model_name\n",
         "\n",
         "# optimized for Tesla T4\n",
         "if length > 700:\n",
@@ -193,7 +205,7 @@
         "             size=(800,480), hbondCutoff=4.0,\n",
         "             Ls=None,\n",
         "             animate=False):\n",
-        "  \n",
+        "\n",
         "  if chains is None:\n",
         "    chains = 1 if Ls is None else len(Ls)\n",
         "  view = py3Dmol.view(js='https://3dmol.org/build/3Dmol.js', width=size[0], height=size[1])\n",
@@ -215,7 +227,7 @@
         "    view.addStyle({'and':[{'resn':\"GLY\"},{'atom':'CA'}]},\n",
         "                  {'sphere':{'colorscheme':f\"WhiteCarbon\",'radius':0.3}})\n",
         "    view.addStyle({'and':[{'resn':\"PRO\"},{'atom':['C','O'],'invert':True}]},\n",
-        "                  {'stick':{'colorscheme':f\"WhiteCarbon\",'radius':0.3}})  \n",
+        "                  {'stick':{'colorscheme':f\"WhiteCarbon\",'radius':0.3}})\n",
         "  if show_mainchains:\n",
         "    BB = ['C','O','N','CA']\n",
         "    view.addStyle({'atom':BB},{'stick':{'colorscheme':f\"WhiteCarbon\",'radius':0.3}})\n",