• File size measurements show the distribution of size of files.
• Files are classified in four categories based on their size (lines of code): 1-100 (very small files), 101-200 (small files), 201-500 (medium size files), 501-1000 (long files), 1001+(very long files).
• It is a good practice to keep files small. Long files may become "bloaters", code that have increased to such gargantuan proportions that they are hard to work with.

• There are 1,404 files with 654,831 lines of code.
• 264 very long files (387,155 lines of code)
• 224 long files (170,070 lines of code)
• 156 medium size files (52,641 lines of codeclsfd_ftr_w_mp_ins)
• 156 small files (21,293 lines of code)
• 604 very small files (23,672 lines of code)

There are 692 files with lines longer than 120 characters. In total, there are 26745 long lines.

File	# lines	# units	# long lines
sagemaker-lineage-multihop-queries_outputs.ipynb in archived	4205	-	1297
bloom-z-176b-few-shot-and-zero-shot-learning.ipynb in archived	3701	-	228
sm-pipelines_preprocess_train_evaluate_batch_transform.ipynb in ml_ops/sm-pipelines_preprocess_train_evaluate_batch_transform	3521	-	158
sm-model_monitor_introduction.ipynb in deploy_and_monitor/sm-model_monitor_introduction	2443	-	138
xgboost_customer_churn_studio.ipynb in archived/getting_started	3904	-	129
sm-ground_truth_chained_streaming_labeling_job.ipynb in prepare_data	1863	-	121
BERTtopic_extending_container.ipynb in archived/pytorch_extend_container_train_deploy_bertopic	1395	-	119
sm-ground_truth_object_detection_example.ipynb in prepare_data/sm-ground_truth_object_detection_example	2114	-	119
inference-pipeline.ipynb in archived/inference_pipeline_custom_containers	1184	-	118
sm-marketplace_building_your_own_container_as_package.ipynb in build_and_train_models/sm-marketplace_building_your_own_container_as_package	1436	-	115
from_unlabeled_data_to_deployed_machine_learning_model_ground_truth_demo_image_classification.ipynb in archived	1826	-	112
sm-clarify_fairness_and_explainability_bring_your_own_container.ipynb in responsible_ai	1404	-	100
sm-clarify_time_series_bring_your_own_model.ipynb in responsible_ai/sm-clarify_time_series_bring_your_own_model	1465	-	97
recommender_system_with_implicit_bpr.ipynb.ipynb in archived/implicit_bpr	1070	-	96
SEC_Retrieval_Summarizer_Scoring.ipynb in archived	2025	-	95
SageMaker-Monitoring-Feature-Attribution-Drift-for-Endpoint.ipynb in archived/fairness_and_explainability_jsonlines	1541	-	93
sm-ground_truth_3d_pointcloud_labeling.ipynb in prepare_data	841	-	93
sm-introduction_to_ip_insights.ipynb in build_and_train_models/sm-introduction_to_ip_insights	1148	-	92
huggingface_sentiment_outputs.ipynb in archived/huggingface_sentiment_classification	3518	-	91
sm-pipelines_selective_execution.ipynb in ml_ops/sm-pipelines_selective_execution	2177	-	89
sm-ground_truth_pretrained_model_labeling.ipynb in prepare_data	2028	-	88
creative-writing-using-gpt-2-text-generation.ipynb in archived/creative-writing-using-gpt-2-text-generation	1120	-	87
sm-jumpstart_stable_diffusion_text_to_image.ipynb in generative_ai	1783	-	87
sm-clarify_model_bias_monitor_batch_transform.ipynb in deploy_and_monitor/sm-clarify_model_bias_monitor_batch_transform	1415	-	84
kohya-ss-fine-tuning.ipynb in archived/text-to-image-fine-tuning	446	-	84
smp-train-gptj-sharded-data-parallel-tp.ipynb in archived/smp-train-gptj-sharded-data-parallel-tp	1679	-	83
preprocessing-audio-data-using-a-machine-learning-model.ipynb in archived/preprocessing-audio-data-using-a-machine-learning-model	965	-	83
evaluating_aws_marketplace_models_for_person_counting_use_case.ipynb in archived/evaluating_aws_marketplace_models_for_person_counting_use_case	1593	-	83
deep_demand_forecast.ipynb in archived/deep_demand_forecasting	3203	-	82
sm-ground_truth_video_quality_metrics.ipynb in prepare_data/sm-ground_truth_video_quality_metrics	1468	-	82
sm-scikit_build_your_own_container.ipynb in build_and_train_models/sm-scikit_build_your_own_container	718	-	79
rapids_sagemaker_hpo.ipynb in archived/rapids_bring_your_own	1449	-	79
sm-jumpstart_llama_2_chat_completion.ipynb in generative_ai	1531	-	79
LDA-Science.ipynb in archived/scientific_details_of_algorithms/lda_topic_modeling	1154	-	78
Dashboard_SEC_Filings.ipynb in archived/nlp_score_dashboard_sec	1131	-	78
sm-pipelines_lambda_step.ipynb in ml_ops/sm-pipelines_lambda_step	2047	-	78
huggingface_sentiment_parallel_batch.ipynb in archived/sentiment_parallel_batch	1967	-	77
sm-batch_transform_pca_dbscan_movie_clusters.ipynb in deploy_and_monitor/sm-batch_transform_pca_dbscan_movie_clusters	1095	-	75
1_cust_churn_dataprep.ipynb in archived/customer_churn	1939	-	75
OpenChat-streaming_tgi.ipynb in archived/workshops	1159	-	75
sm-jumpstart_foundation_llama_3_2_3b_finetuning.ipynb in generative_ai	859	-	75
sm-ground_truth_create_streaming_labeling_job.ipynb in prepare_data	1092	-	75
nlp_company_earnings_analysis_pipeline.ipynb in archived/nlp_mlops_company_sentiment	1581	-	72
r_xgboost_hpo_batch_transform.ipynb in archived	1029	-	72
gluon_recommender_system.ipynb in archived/gluon_recommender_system	1046	-	72
sentiment-analysis-tf-distributed-training-bringyourownscript.ipynb in archived/sagemaker-debugger/tensorflow_nlp_sentiment_analysis	2267	-	72
sm-jumpstart_private_model_hub_import_llama3-8B.ipynb in build_and_train_models/sm-jumpstart_private_model_hub_import	1740	-	71
huggingface-inference-recommender.ipynb in archived/huggingface-inference-recommender	1749	-	71
3D-point-cloud-input-data-processing.ipynb in archived	1098	-	71
tf-cloudwatch-inference-recommender.ipynb in archived/tensorflow-cloudwatch	1635	-	70