• 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 20 files with 37,122 lines of code.
• 11 very long files (33,993 lines of code)
• 3 long files (1,866 lines of code)
• 2 medium size files (881 lines of codeclsfd_ftr_w_mp_ins)
• 2 small files (319 lines of code)
• 2 very small files (63 lines of code)

There are 18 files with lines longer than 120 characters. In total, there are 625 long lines.

File	# lines	# units	# long lines
115_introducing_contrastive_search.ipynb in notebooks	1165	-	115
02_how_to_generate.ipynb in notebooks	786	-	72
56_fine_tune_segformer.ipynb in notebooks	6016	-	67
01_how_to_train.ipynb in notebooks	1567	-	64
53_constrained_beam_search.ipynb in notebooks	513	-	51
111_fine_tune_whisper.ipynb in notebooks	1339	-	51
10_tf_serving.ipynb in notebooks	1137	-	47
HuggingFace_int8_demo.ipynb in notebooks	6124	-	32
112_vertex_ai_vision.ipynb in notebooks	1022	-	25
graphml-classification.ipynb in notebooks	6812	-	23
80_getting_started_with_embeddings.ipynb in notebooks	2494	-	17
111_tf_serving_vision.ipynb in notebooks	1612	-	16
123_clipseg-zero-shot.ipynb in notebooks	567	-	16
fl-with-flower.ipynb in notebooks	386	-	11
unified-tool-calling.ipynb in notebooks	4705	-	7
13_pytorch_xla.ipynb in notebooks	189	-	5
91_tf_xla_generate.ipynb in notebooks	130	-	5
run_clm_no_trainer.py in assets/62_pytorch_fsdp	495	2	1