Instruct-TK-Infer.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "870e8279",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-01-31 14:07:58.011991: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 AVX512F FMA\n",
      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import json\n",
    "\n",
    "import torch\n",
    "import tqdm\n",
    "\n",
    "from transformers import T5Tokenizer, T5ForConditionalGeneration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "677130fd",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = json.load(open(\"Complete_dataset/test.json\"))\n",
    "files = os.listdir(\"Complete_dataset/CT json/\")\n",
    "files.remove(\".DS_Store\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d5df4e00",
   "metadata": {},
   "outputs": [],
   "source": [
    "files_data = {file[:-5]:json.load(open(f\"Complete_dataset/CT json/{file}\")) for file in files}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "07636837",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_expanded = []\n",
    "for _id, value in data.items():\n",
    "    temp = {}\n",
    "    temp[\"id\"] = _id\n",
    "    p_nctid = value[\"Primary_id\"]\n",
    "    s_nctid = value.get(\"Secondary_id\")\n",
    "    section_id = value[\"Section_id\"]\n",
    "    statement = value[\"Statement\"]\n",
    "    primary_evidence = files_data[p_nctid][section_id]\n",
    "    temp[\"statement\"] = statement\n",
    "    temp[\"primary_evidence\"] = primary_evidence\n",
    "#     temp[\"label\"] = value[\"Label\"]\n",
    "    \n",
    "    if s_nctid is not None:\n",
    "        secondary_evidence = files_data[s_nctid][section_id]\n",
    "        temp[\"secondary_evidence\"] = secondary_evidence\n",
    "    \n",
    "    data_expanded.append(temp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e0a6c139",
   "metadata": {},
   "outputs": [],
   "source": [
    "tokenizer = T5Tokenizer.from_pretrained(\"allenai/tk-instruct-11b-def\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "dce56a86",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "198521ab212d4c0a8a5609f4e37a7b09",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model = T5ForConditionalGeneration.from_pretrained(\"allenai/tk-instruct-11b-def\", device_map=\"auto\", torch_dtype=torch.bfloat16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ab1349c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_input_text(premise, hypothesis):\n",
    "    return f\"Definition: In this task, you are given a premise and hypothesis. The task is to classify them into two categories: 'Entailment' if the hypothesis supports the premise, 'Contradiction' if it opposes the premise. \\nNow complete the following example -\\nInput: {premise} \\n Question: Does this imply that {hypothesis}?  Entailment or Contradiction?\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a307dd6d",
   "metadata": {},
   "outputs": [],
   "source": [
    "samples = []\n",
    "for sample in data_expanded:\n",
    "    primary_evidence = \"\".join(sample['primary_evidence'])\n",
    "    sentence = f\"Primary trial evidence are {primary_evidence}\"\n",
    "    secondary_evidence = sample.get(\"secondary_evidence\")\n",
    "    if secondary_evidence:\n",
    "        secondary_evidence = \"\".join(sample['secondary_evidence'])\n",
    "        sentence = f\"{sentence} Secondary trial evidence are {secondary_evidence}\"\n",
    "    input_text = get_input_text(sentence, sample['statement'])\n",
    "    temp = {\"text\":input_text, \"label\":0}\n",
    "    samples.append(temp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "f5d62610",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 500/500 [02:34<00:00,  3.24it/s]\n"
     ]
    }
   ],
   "source": [
    "labels = []\n",
    "pred = []\n",
    "for sample in tqdm.tqdm(samples):\n",
    "    labels.append(sample[\"label\"])\n",
    "    input_ids = tokenizer(sample[\"text\"], return_tensors=\"pt\",).input_ids.to(\"cuda\")\n",
    "    outputs = model.generate(input_ids)\n",
    "    pred.append(tokenizer.decode(outputs[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "708cd824",
   "metadata": {},
   "outputs": [
    {
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       " '<pad> Contradiction</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Contradiction</s>',\n",
       " '<pad> Entailment</s>',\n",
       " '<pad> Contradiction</s>']"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "32f3b8fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "pred = [p[5:][:-4].strip() for p in pred]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "5d349880",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Entailment', 'Contradiction'}\n"
     ]
    }
   ],
   "source": [
    "print(set(pred))\n",
    "from collections import Counter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "12564dd1",
   "metadata": {},
   "outputs": [],
   "source": [
    "pred = [p.capitalize() for p in pred]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "6b9a6d6e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Counter({'Entailment': 137, 'Contradiction': 363})"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Counter(pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "6fbbb1d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "prediction_dict = {}\n",
    "for _id,pred_x in zip(data, pred):\n",
    "    prediction_dict[str(_id)] = {\"Prediction\":pred_x}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "fdfcff67",
   "metadata": {},
   "outputs": [],
   "source": [
    "json.dump(prediction_dict, open(\"results.json\",'w'),indent=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "e87cce1e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  adding: results.json (deflated 74%)\n"
     ]
    }
   ],
   "source": [
    "!zip zeroshot_instruct_11b_2.zip results.json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "37a17ffd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'9f978634-637c-472f-a588-6f4bb2fb121f': {'Prediction': 'Contradiction'},\n",
       " '20b34e62-97c2-4ca0-bb1d-7824dab0b8bb': {'Prediction': 'Contradiction'},\n",
       " '893a5337-2aa9-4a87-a020-4c2f03cd4aea': {'Prediction': 'Entailment'},\n",
       " 'd401affc-f081-4eee-bd61-d109cc88f6de': {'Prediction': 'Entailment'},\n",
       " '791790a6-187b-4e4b-be5f-9e5304e9ec2c': {'Prediction': 'Contradiction'},\n",
       " 'b95b7438-ec16-4d4d-826d-5891e7982b36': {'Prediction': 'Entailment'},\n",
       " '4988cb16-7dbb-4847-84e0-4a7957b32c72': {'Prediction': 'Contradiction'},\n",
       " 'e244fc3a-53b3-4158-99c5-a45afc726af6': {'Prediction': 'Contradiction'},\n",
       " '56530063-b408-47f2-8421-6be825f5559c': {'Prediction': 'Entailment'},\n",
       " 'd3379655-55b7-4e58-88c2-c3cd3e8cb557': {'Prediction': 'Contradiction'},\n",
       " '7bf988b4-5e6f-41c4-bef6-7b3549dd58d9': {'Prediction': 'Contradiction'},\n",
       " '84915e35-a8c9-4d26-ad09-4b1df48a6df8': {'Prediction': 'Entailment'},\n",
       " '64df451c-f868-49e6-9b4e-a325e62ce837': {'Prediction': 'Contradiction'},\n",
       " 'dc4765a3-6168-4594-969b-3ce5ea7dc02a': {'Prediction': 'Contradiction'},\n",
       " '9c2ca035-d531-4d44-876e-6ed9f2d3f76b': {'Prediction': 'Entailment'},\n",
       " '7238ddd4-eade-4b88-8933-0c3df5be9875': {'Prediction': 'Contradiction'},\n",
       " 'aeddc485-09b1-4ddc-9a45-3a8bf0bec2c3': {'Prediction': 'Contradiction'},\n",
       " '204d5293-d6e5-452a-8961-3b76d6be35c9': {'Prediction': 'Entailment'},\n",
       " '4ed1c5fd-58e5-4fe8-97b1-59ed509ccb10': {'Prediction': 'Entailment'},\n",
       " '6d0812b9-f9bd-4cd6-82aa-9c272eba23be': {'Prediction': 'Contradiction'},\n",
       " 'fd0fa999-2f1c-400d-977d-2d45dd9c358c': {'Prediction': 'Contradiction'},\n",
       " '571d4650-e64b-4cb2-b719-0d7064e51745': {'Prediction': 'Contradiction'},\n",
       " '4437aa5b-4b4e-4eb4-a258-e7f17dc8f363': {'Prediction': 'Contradiction'},\n",
       " 'd7abbd7d-a767-49c0-bc99-1c28074eac21': {'Prediction': 'Contradiction'},\n",
       " '54c7e880-a1bf-4206-9573-1c994932ba15': {'Prediction': 'Contradiction'},\n",
       " 'f9f0ba74-16e0-4790-afa0-b7616b256e5e': {'Prediction': 'Entailment'},\n",
       " '412583db-ce19-451d-a804-3837e4dcaea3': {'Prediction': 'Contradiction'},\n",
       " 'bca4c94d-4a49-4e05-82ed-0d5c9707685b': {'Prediction': 'Entailment'},\n",
       " '97acf304-2707-4a1b-81e7-339fde2ed0ee': {'Prediction': 'Contradiction'},\n",
       " '21a5f296-5b3c-4860-be64-77ffb8f76501': {'Prediction': 'Entailment'},\n",
       " '8d27bb53-e66e-4eab-bea4-0597fd5760b5': {'Prediction': 'Contradiction'},\n",
       " 'dc60304d-6fd2-4b12-9108-b5ce78454d42': {'Prediction': 'Contradiction'},\n",
       " '328417f9-8f45-4114-82d7-9396b6bc578e': {'Prediction': 'Contradiction'},\n",
       " '40d84c7b-e126-4d6f-9588-eb9c385ca716': {'Prediction': 'Contradiction'},\n",
       " 'b685be77-9c55-4948-99cc-2a249739a233': {'Prediction': 'Entailment'},\n",
       " '5fbee4f6-43fc-45a7-88c4-3dcd5ff21053': {'Prediction': 'Entailment'},\n",
       " '8127d46a-3a48-4173-8d00-75e949755a74': {'Prediction': 'Contradiction'},\n",
       " '576967ff-d2bb-4d1c-b2a1-8516ceb7a519': {'Prediction': 'Contradiction'},\n",
       " 'fd334e71-2bbe-4138-b578-2ab848686045': {'Prediction': 'Contradiction'},\n",
       " 'a72ddea5-ee4b-4895-bd8c-10b4a143c3f8': {'Prediction': 'Contradiction'},\n",
       " '6c29e8c1-36ca-4e6e-b4dc-f1e91b98e546': {'Prediction': 'Contradiction'},\n",
       " 'd1118512-9c0b-4480-ab67-d4e0c7de390d': {'Prediction': 'Contradiction'},\n",
       " 'd35e9b96-20fc-4778-a7db-e87c861c4938': {'Prediction': 'Contradiction'},\n",
       " '25b01c06-612c-4cfb-b30b-50ebe4d98750': {'Prediction': 'Contradiction'},\n",
       " '1a76bce8-07e2-4b30-adc8-3c095f0d62b3': {'Prediction': 'Contradiction'},\n",
       " '23f84ae0-fd01-4799-8872-118e22a015e8': {'Prediction': 'Contradiction'},\n",
       " 'c2aea351-6ce5-4d26-9ba5-2632c6367b93': {'Prediction': 'Entailment'},\n",
       " '388cc99c-4cb3-4ff9-9496-07f4a6bf6ac7': {'Prediction': 'Contradiction'},\n",
       " '5af6aa8c-69f5-44a5-9c7c-6c94a0fda6e8': {'Prediction': 'Contradiction'},\n",
       " '455d059c-c3c4-4a09-be0d-a14b9568a0d2': {'Prediction': 'Entailment'},\n",
       " '6d37ed53-a6e4-403e-8b93-9954a6486dbc': {'Prediction': 'Entailment'},\n",
       " 'e530eed4-ee8b-4a7f-bb36-5ce9ea7ddebe': {'Prediction': 'Contradiction'},\n",
       " '41a0138d-7084-40d9-99ae-24db9e84acce': {'Prediction': 'Entailment'},\n",
       " '11cb71ed-1304-42f0-b416-3679c3e9e1b3': {'Prediction': 'Contradiction'},\n",
       " '6ddf4b5b-69e2-46e1-b032-69c3173fd8ef': {'Prediction': 'Entailment'},\n",
       " '9349c7c8-7771-4dfc-8981-3c8d84ac5236': {'Prediction': 'Entailment'},\n",
       " '4e91cee2-910e-4f08-8a85-1f13545391c3': {'Prediction': 'Contradiction'},\n",
       " '18c281a1-43bd-47f5-9534-feddfcf0a282': {'Prediction': 'Contradiction'},\n",
       " 'dd3d2183-d062-41ed-af63-ae475f2246ec': {'Prediction': 'Contradiction'},\n",
       " '711fdd40-52ec-401c-90fc-5a11de547ab6': {'Prediction': 'Entailment'},\n",
       " '49b3b463-a496-404a-a3a5-07cd7d4aaa92': {'Prediction': 'Entailment'},\n",
       " '43b9c2c8-0785-4885-901b-91a1f893858f': {'Prediction': 'Entailment'},\n",
       " '43989f85-a059-4dc7-a805-16e081706b2f': {'Prediction': 'Entailment'},\n",
       " '282a33db-aed6-4daa-bea6-299f424914bb': {'Prediction': 'Contradiction'},\n",
       " '646691ba-ad29-479f-81dc-131d9710c23b': {'Prediction': 'Contradiction'},\n",
       " 'a0c1da21-1e1f-493b-81e9-4ef133c20090': {'Prediction': 'Contradiction'},\n",
       " '439b1eca-f583-4a2b-bd8e-0baae97b4c15': {'Prediction': 'Contradiction'},\n",
       " 'e12e5ed1-9a64-4183-9b9d-419e6679ab3d': {'Prediction': 'Entailment'},\n",
       " '73849f1e-31c6-40c5-ab5c-35d0990ceac2': {'Prediction': 'Entailment'},\n",
       " 'f53c5344-36d7-459f-9f84-300e19decced': {'Prediction': 'Contradiction'},\n",
       " '77fd9a89-4d9b-40ab-b4ad-fcf554ca68d2': {'Prediction': 'Entailment'},\n",
       " '99433bba-fce5-4b0a-a076-1f699b51472d': {'Prediction': 'Contradiction'},\n",
       " '135763e3-70fd-478d-991c-717d6ed55bb3': {'Prediction': 'Entailment'},\n",
       " '6cbfc99b-6531-412f-bd30-b4a803983831': {'Prediction': 'Entailment'},\n",
       " '6a3053ef-4495-4c18-9da7-68cf5ed254e0': {'Prediction': 'Contradiction'},\n",
       " '217b0362-9dd0-4f10-8ca5-c097688bb738': {'Prediction': 'Contradiction'},\n",
       " 'd88235dd-c37b-4971-9c1f-42b282ff41c1': {'Prediction': 'Contradiction'},\n",
       " 'e6bbed17-0fdf-4008-b56e-4d901490ce1a': {'Prediction': 'Entailment'},\n",
       " 'f1f9d4b4-4877-49ad-a2e2-f53efbe40ef9': {'Prediction': 'Entailment'},\n",
       " '8393ad3d-8521-4316-b69e-64910d8af5e7': {'Prediction': 'Contradiction'},\n",
       " 'cca11232-84c4-44e1-89f1-b57b28643dce': {'Prediction': 'Contradiction'},\n",
       " 'cb36e435-6dc9-4e7b-939b-9da6ceef2a49': {'Prediction': 'Contradiction'},\n",
       " '7ce21c0f-ad55-4ff7-a180-5e418fe9afc8': {'Prediction': 'Contradiction'},\n",
       " '42c38d71-6a83-4967-ad81-ec38c6b5aafd': {'Prediction': 'Entailment'},\n",
       " '6c5ebc06-00c4-4cf5-8912-93972ed5a49b': {'Prediction': 'Entailment'},\n",
       " '32cc173a-b271-47c9-997d-df17ce1c7494': {'Prediction': 'Entailment'},\n",
       " 'b742bc02-cd24-4ae7-b8b8-2a57bbd60d14': {'Prediction': 'Entailment'},\n",
       " '334b5f86-50c5-4711-994d-31ed67dd4282': {'Prediction': 'Contradiction'},\n",
       " '04178e95-d808-4a96-ab85-61eb52c17720': {'Prediction': 'Contradiction'},\n",
       " '18d3b58f-42ca-4178-adb6-4a5f0c9fafde': {'Prediction': 'Entailment'},\n",
       " 'cfa6601b-af52-4eee-883c-89d42b73e02b': {'Prediction': 'Entailment'},\n",
       " 'f58fda4c-f4fd-44a7-8a0f-5d3a16929709': {'Prediction': 'Entailment'},\n",
       " 'e52afcaa-e5d8-4a1f-ae39-8572a64b0aee': {'Prediction': 'Entailment'},\n",
       " '96042d49-2f5a-44af-8899-2d5ba24c0f6f': {'Prediction': 'Entailment'},\n",
       " '587e611a-9c3b-4557-b3ca-56a7dcc6ce1b': {'Prediction': 'Contradiction'},\n",
       " 'ea3a7d64-b464-4633-a198-794a4a45b201': {'Prediction': 'Entailment'},\n",
       " '58165e03-4aa6-4d0c-8256-dbc92ee900c4': {'Prediction': 'Contradiction'},\n",
       " 'fa7b34e2-75e6-4bc4-a154-99be5bd6b381': {'Prediction': 'Entailment'},\n",
       " '7b9338a5-d3a8-405f-a197-736caf32c455': {'Prediction': 'Contradiction'},\n",
       " '8f078a17-14cd-4bbc-a9b6-b377ffa077b5': {'Prediction': 'Contradiction'},\n",
       " '2d36fa83-b68c-420e-873f-e69374d0741f': {'Prediction': 'Contradiction'},\n",
       " '6e1489a6-3a42-4b52-b690-fb1dd8892749': {'Prediction': 'Contradiction'},\n",
       " 'de6b5ea7-b593-43b7-8fe0-358991878e86': {'Prediction': 'Entailment'},\n",
       " 'fe5928a4-1a0c-4c41-9b85-8d7785a8ab4c': {'Prediction': 'Contradiction'},\n",
       " '827af363-cfd3-4233-9029-e8c7e053c661': {'Prediction': 'Contradiction'},\n",
       " '3c9a4b79-1f51-477a-a5b6-b69f76aeedf8': {'Prediction': 'Contradiction'},\n",
       " '98b04dac-b155-4afd-8855-03ed818df5d9': {'Prediction': 'Entailment'},\n",
       " '7eeeed55-fe37-47ae-be62-e50557ccaed1': {'Prediction': 'Entailment'},\n",
       " 'cbc96b9d-b39c-4fbe-b8a7-e7df7490881b': {'Prediction': 'Contradiction'},\n",
       " '2a05996c-d5fb-4aa8-9654-fb1d27180888': {'Prediction': 'Contradiction'},\n",
       " 'da24d6fd-1363-489b-ac5a-f44dbe622c5d': {'Prediction': 'Contradiction'},\n",
       " '437d5311-f0fd-4d61-82a2-5db0d07415f6': {'Prediction': 'Entailment'},\n",
       " 'af0e8d9b-f748-424d-a4e7-6bb3bf0ee7a2': {'Prediction': 'Entailment'},\n",
       " '2bd78232-4872-4d66-ade9-836190b86e1d': {'Prediction': 'Contradiction'},\n",
       " '80a26581-a95c-4c22-864f-93425b1fc165': {'Prediction': 'Entailment'},\n",
       " '4c926c31-8786-47b0-a032-1d59f759bca5': {'Prediction': 'Entailment'},\n",
       " '62384871-8eb2-414b-8cc9-e756a188e19e': {'Prediction': 'Contradiction'},\n",
       " 'a6e81477-f863-4a83-9007-fd2f1f5c6781': {'Prediction': 'Contradiction'},\n",
       " '2312576f-7c8d-4fcd-80e8-42cf3d81dd04': {'Prediction': 'Contradiction'},\n",
       " '8f4d4e78-5e46-47b6-865c-ad6b689d69e0': {'Prediction': 'Contradiction'},\n",
       " 'a8268e5e-d758-4dcf-8dd9-78c2016bc7f6': {'Prediction': 'Entailment'},\n",
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      "\u001b[1;31mnotebook controller is DISPOSED. \n",
      "\u001b[1;31mView Jupyter <a href='command:jupyter.viewOutput'>log</a> for further details."
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