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"y1 = [e[0] for e in evaluations.values() if len(e) == 2]\n",
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"X = [s for s in evaluations.keys()]\n",
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"array([0.41666667, 0.25 , 0.16666667, 0.41666667, 0.5 ])"
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" ('classifier', LinearSVC(random_state=42))])"
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"outputs": [],
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"source": [
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"from typing import List\n",
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{
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"cell_type": "code",
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"\u001b[38;5;39mFetching cached versions of scibert-highlights\u001b[0m\n",
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"\u001b[38;5;39mLatest version of scibert-highlights is 0 (from versions: 0)\u001b[0m\n",
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"\u001b[38;5;226mEnvironment variable ENVIRONMENT is not set, defaulting to development mode ‼️\u001b[0m\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"\u001b[38;5;226mCannot find credentials files, defaulting to using ParallelTinyDbDriver\u001b[0m\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"\u001b[38;5;226mThe selected tracing database (ParallelTinyDbDriver) is not recommended for production\u001b[0m\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"\u001b[38;5;226mCannot find credentials files, defaulting to using LargeFileLocal\u001b[0m\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"\u001b[38;5;39mGreatAI (v0.1.11): configured ✅\u001b[0m\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"\u001b[38;5;39m 🔩 tracing_database: ParallelTinyDbDriver\u001b[0m\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"\u001b[38;5;39m 🔩 large_file_implementation: LargeFileLocal\u001b[0m\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"\u001b[38;5;39m 🔩 is_production: False\u001b[0m\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"\u001b[38;5;39m 🔩 should_log_exception_stack: True\u001b[0m\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"\u001b[38;5;39m 🔩 prediction_cache_size: 512\u001b[0m\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"\u001b[38;5;39m 🔩 dashboard_table_size: 50\u001b[0m\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"\u001b[38;5;226mYou still need to check whether you follow all best practices before trusting your deployment.\u001b[0m\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"\u001b[38;5;226m> Find out more at https://se-ml.github.io/practices\u001b[0m\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"\u001b[38;5;39mFetching cached versions of scibert-highlights\u001b[0m\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"\u001b[38;5;39mLatest version of scibert-highlights is 0 (from versions: 0)\u001b[0m\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"\u001b[38;5;39mFile scibert-highlights-0 found in cache\u001b[0m\n"
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]
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}
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"execution_count": 3,
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"id": "cell-9",
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"metadata": {},
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-10-28T22:48:11.257418Z",
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"iopub.status.busy": "2026-10-28T22:48:11.257269Z",
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"iopub.status.idle": "2026-10-28T22:48:11.289789Z",
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"shell.execute_reply": "2026-10-28T22:48:11.289400Z"
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}
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},
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"outputs": [],
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"source": [
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"from great_ai import GreatAI\n",
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"execution_count": 4,
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"shell.execute_reply": "2026-10-28T22:48:11.803126Z"
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}
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},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"W1028 12:49:11.667000 52910 torch/distributed/elastic/multiprocessing/redirects.py:35] NOTE: Redirects are currently not supported in MacOs.\n"
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"W1028 22:48:11.714000 21400 .venv/lib/python3.13/site-packages/torch/distributed/elastic/multiprocessing/redirects.py:35] NOTE: Redirects are currently not supported in MacOs.\n"
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"version_minor": 0
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},
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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Reference in a new issue