Datasets:

egolimblevskaia
/

weightlens-gemma-2-2b-transcoder-descriptions

Error code:   DatasetGenerationError
Exception:    TypeError
Message:      Couldn't cast array of type struct<contribution: double, from_feature_idx: int64, from_layer: int64, relative_contribution: double> to null
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1887, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 675, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2224, in cast_table_to_schema
                  cast_array_to_feature(
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1795, in wrapper
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2052, in cast_array_to_feature
                  casted_array_values = _c(array.values, feature.feature)
                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1797, in wrapper
                  return func(array, *args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2086, in cast_array_to_feature
                  return array_cast(
                         ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1797, in wrapper
                  return func(array, *args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1950, in array_cast
                  raise TypeError(f"Couldn't cast array of type {_short_str(array.type)} to {_short_str(pa_type)}")
              TypeError: Couldn't cast array of type struct<contribution: double, from_feature_idx: int64, from_layer: int64, relative_contribution: double> to null
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1347, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 884, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 947, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1736, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1919, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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feature dict	embedding dict	output_logits dict	feature_to_feature_contributions list	total_input_invariant_detected_contribution float64	total_input_invariant_contribution int64	description_soft list	description list	validation bool	validation_soft int64
{ "feature_idx": 0, "layer": 0 }	{ "positive_tokens_activation": [ 15.125, 9.875, 8.375, 8.375 ], "top_negative_tokens": [ " Baillargeon", "pannt" ], "top_negative_tokens_contribution": [ -33.5, -29.125 ], "top_negative_tokens_ids": [ 223296, 149711 ], "top_negative_tokens_relative_contribution...	{ "top_negative_tokens": [], "top_positive_tokens": [ "\n", "\n\n", " " ] }	[]	0.000078	1,679,360	[ " Club", " [*]", " club", " sold" ]	[ " Club", " [*]", " club", " sold" ]	true	1
{ "feature_idx": 1, "layer": 0 }	{ "positive_tokens_activation": [ 2.59375, 1.6875, 1.625, 1.5625, 1.78125 ], "top_negative_tokens": [ "TypedDataSet", " dieux", " الدولى" ], "top_negative_tokens_contribution": [ -36.5, -30.625, -30.375 ], "top_negative_tokens_ids": [ 82947, 169933, ...	{ "top_negative_tokens": [ "<bos>", "Para", " para", " Para" ], "top_positive_tokens": [ "+#+#", "KommentareTeilen" ] }	[]	0.000091	1,228,800	[ "Lähteet", "Przypisy", "]--;", "endwhile", "numerusform" ]	[ "Lähteet", "Przypisy", "]--;", "endwhile", "numerusform" ]	true	1
{ "feature_idx": 2, "layer": 0 }	{ "positive_tokens_activation": [ 4.125, 3.859375 ], "top_negative_tokens": [ "<eos>", " resourceCulture" ], "top_negative_tokens_contribution": [ -11.8125, -11.25 ], "top_negative_tokens_ids": [ 1, 94695 ], "top_negative_tokens_relative_contribution": [ 0.000017478...	{ "top_negative_tokens": [ "ing", "<bos>", "engertian" ], "top_positive_tokens": [] }	[]	0.000062	675,840	[ " Efq", " myſelf" ]	[ " Efq", " myſelf" ]	true	1
{ "feature_idx": 3, "layer": 0 }	{ "positive_tokens_activation": [ 11.375, 10.25, 11.0625 ], "top_negative_tokens": [ "хьтан" ], "top_negative_tokens_contribution": [ -37.5 ], "top_negative_tokens_ids": [ 224805 ], "top_negative_tokens_relative_contribution": [ 0.000024479340936522934 ], "top_positive_...	{ "top_negative_tokens": [ "<bos>", "\n\n", "\n", "'" ], "top_positive_tokens": [ "transQ", "Demografía", " متعلقه", "principalTable" ] }	[]	0.000059	1,531,904	[ " beloved", " fresh", " loved" ]	[ " beloved", " fresh", " loved" ]	true	1
{ "feature_idx": 4, "layer": 0 }	{ "positive_tokens_activation": [], "top_negative_tokens": [ "TagHelper", "+#+", "NameInMap" ], "top_negative_tokens_contribution": [ -52.75, -52.75, -51.25 ], "top_negative_tokens_ids": [ 18789, 74073, 148363 ], "top_negative_tokens_relative_contribution": [ 0.00...	{ "top_negative_tokens": [ "<bos>" ], "top_positive_tokens": [] }	[]	0	2,588,672	null	null	false	0
{ "feature_idx": 5, "layer": 0 }	{ "positive_tokens_activation": [], "top_negative_tokens": [], "top_negative_tokens_contribution": [], "top_negative_tokens_ids": [], "top_negative_tokens_relative_contribution": [], "top_positive_token_ids": [], "top_positive_tokens": [], "top_positive_tokens_contribution": [], "top_positive_tokens_r...	{ "top_negative_tokens": [ "<bos>" ], "top_positive_tokens": [ "ophone", "istics", "arbon" ] }	[]	0	2,195,456	null	null	false	0
{ "feature_idx": 6, "layer": 0 }	{ "positive_tokens_activation": [], "top_negative_tokens": [ "Rhestr", " Spisak", "", "帖最后由" ], "top_negative_tokens_contribution": [ -34, -32.75, -30.75, -30.625 ], "top_negative_tokens_ids": [ 100326, 136551, 244842, 231598 ], "top_negative_tokens_relat...	{ "top_negative_tokens": [], "top_positive_tokens": [] }	[]	0	1,933,312	null	null	false	0
{ "feature_idx": 7, "layer": 0 }	{ "positive_tokens_activation": [ 11.875, 12.125, 10.5 ], "top_negative_tokens": [ "出版年", " Económica", "setupUi", "sidemargin" ], "top_negative_tokens_contribution": [ -38.75, -36.25, -35, -33.75 ], "top_negative_tokens_ids": [ 151160, 226953, 16849...	{ "top_negative_tokens": [], "top_positive_tokens": [ " ", " the", " a" ] }	[]	0.000056	1,671,168	[ " motivated", " motivation", " tape" ]	[ " motivated", " motivation", " tape" ]	true	1
{ "feature_idx": 8, "layer": 0 }	{ "positive_tokens_activation": [ 0, 0, 0 ], "top_negative_tokens": [ "исленность" ], "top_negative_tokens_contribution": [ -28.625 ], "top_negative_tokens_ids": [ 183529 ], "top_negative_tokens_relative_contribution": [ 0.00002806636621244251 ], "top_positive_token_ids...	{ "top_negative_tokens": [ "<bos>", " unknownFields", "'", "s" ], "top_positive_tokens": [ " démocr", "AnchorStyles" ] }	[]	0.000044	1,019,904	null	null	false	0
{ "feature_idx": 9, "layer": 0 }	{ "positive_tokens_activation": [ 5.875, 1.84375 ], "top_negative_tokens": [ " EconPapers", "Vaya", "\\}\\\\" ], "top_negative_tokens_contribution": [ -29.125, -28.625, -28.125 ], "top_negative_tokens_ids": [ 192563, 221865, 207494 ], "top_negative_tokens_re...	{ "top_negative_tokens": [ "ButterKnife", "庁" ], "top_positive_tokens": [ " '{@", ">{@", "بوابة", " JpaRepository" ] }	[]	0.000023	1,368,064	[ " समीक्षक", "peche" ]	[ " समीक्षक", "peche" ]	true	1
{ "feature_idx": 10, "layer": 0 }	{ "positive_tokens_activation": [ 0.875, 6.6875, 5.8125, 6.375 ], "top_negative_tokens": [ " ModelExpression", "fromnode", "AnchorStyles", "DockStyle" ], "top_negative_tokens_contribution": [ -50.25, -42.25, -41, -38.25 ], "top_negative_tokens_ids": [ 15...	{ "top_negative_tokens": [ "<bos>" ], "top_positive_tokens": [ " trí", "出版年", " [*]" ] }	[]	0.000069	1,318,912	[ "########.", "iiiiiiii", "let", "set" ]	[ "########.", "iiiiiiii", "let", "set" ]	true	1
{ "feature_idx": 11, "layer": 0 }	{ "positive_tokens_activation": [ 12.375, 2.625, 3.15625 ], "top_negative_tokens": [], "top_negative_tokens_contribution": [], "top_negative_tokens_ids": [], "top_negative_tokens_relative_contribution": [], "top_positive_token_ids": [ 562, 174788, 187646 ], "top_positive_tokens...	{ "top_negative_tokens": [], "top_positive_tokens": [ "<bos>" ] }	[]	0.000063	1,458,176	[ "AndEndTag", "bootstrapcdn", "ot" ]	[ "AndEndTag", "bootstrapcdn", "ot" ]	true	1
{ "feature_idx": 12, "layer": 0 }	{ "positive_tokens_activation": [ 17.25, 15.625, 13.75, 13.875, 12, 13, 11.875 ], "top_negative_tokens": [ " lenker", "rungsseite", "IUrlHelper" ], "top_negative_tokens_contribution": [ -47.75, -41.5, -41 ], "top_negative_tokens_ids": [ 58058, 68...	{ "top_negative_tokens": [ "\n\n", " " ], "top_positive_tokens": [ "$\")", " $_\"" ] }	[]	0.000122	2,129,920	[ " Meanwhile", " listen", " listened", " listening", " listens", " meanwhile", "Meanwhile" ]	[ " Meanwhile", " listen", " listened", " listening", " listens", " meanwhile", "Meanwhile" ]	true	1
{ "feature_idx": 13, "layer": 0 }	{ "positive_tokens_activation": [ 2.53125, 0 ], "top_negative_tokens": [ "CppCodeGen", "حياته", "حياتها", "EDEFAULT" ], "top_negative_tokens_contribution": [ -35.75, -33.75, -33.25, -31.25 ], "top_negative_tokens_ids": [ 165842, 36137, 121900, 203255...	{ "top_negative_tokens": [ "<bos>" ], "top_positive_tokens": [ ".", " place", " too", " very" ] }	[]	0.000031	1,507,328	[ " how" ]	[ " how" ]	true	1
{ "feature_idx": 14, "layer": 0 }	{ "positive_tokens_activation": [], "top_negative_tokens": [ "+#+#", "aarrggbb", " חיצוניים", " gyhoeddwyd", "webElementXpaths" ], "top_negative_tokens_contribution": [ -42.5, -37.75, -37.75, -37.75, -36.25 ], "top_negative_tokens_ids": [ 183157, 91343, 10...	{ "top_negative_tokens": [ "&=&\\" ], "top_positive_tokens": [ "<bos>", "'" ] }	[]	0	2,260,992	null	null	false	0
{ "feature_idx": 15, "layer": 0 }	{ "positive_tokens_activation": [ 15.875, 13.75, 13.375, 12.375, 11.25, 12 ], "top_negative_tokens": [ "WebVitals", "FormTagHelper" ], "top_negative_tokens_contribution": [ -42.25, -36.25 ], "top_negative_tokens_ids": [ 154156, 117266 ], "top_negative_to...	{ "top_negative_tokens": [ " I" ], "top_positive_tokens": [] }	[]	0.000115	1,736,704	[ " Interval", " cold", " interval", " intervals", "cold", "interval" ]	[ " Interval", " cold", " interval", " intervals", "cold", "interval" ]	true	1
{ "feature_idx": 16, "layer": 0 }	{ "positive_tokens_activation": [ 13.1875, 8.875, 10.4375, 9.4375 ], "top_negative_tokens": [ " noqa", "MigrationBuilder", " ProtoMessage", "complexContent", "ipedi" ], "top_negative_tokens_contribution": [ -39.75, -39.25, -37.25, -36.25, -35.75 ], "...	{ "top_negative_tokens": [], "top_positive_tokens": [ " myſelf" ] }	[]	0.000051	2,023,424	[ " governance", " governing", " protection", " revenue" ]	[ " governance", " governing", " protection", " revenue" ]	true	1
{ "feature_idx": 17, "layer": 0 }	{ "positive_tokens_activation": [], "top_negative_tokens": [ "Tikang", "SharedCtor", "principalTable", " صوتيه", "Personensuche" ], "top_negative_tokens_contribution": [ -33.5, -33.25, -31.75, -31.75, -31.375 ], "top_negative_tokens_ids": [ 122326, 191376, ...	{ "top_negative_tokens": [ "<bos>" ], "top_positive_tokens": [] }	[]	0	1,024,000	null	null	false	0
{ "feature_idx": 18, "layer": 0 }	{ "positive_tokens_activation": [ 0, 2.1875, 2.125 ], "top_negative_tokens": [ "EndContext", "IsContent" ], "top_negative_tokens_contribution": [ -63.5, -60 ], "top_negative_tokens_ids": [ 31280, 65876 ], "top_negative_tokens_relative_contribution": [ 0.00001737...	{ "top_negative_tokens": [ "<bos>", "\n\n", "'" ], "top_positive_tokens": [ " propOrder", "EndContext" ] }	[]	0.000019	3,653,632	[ " return", "return" ]	[ " return", "return" ]	true	1
{ "feature_idx": 19, "layer": 0 }	{ "positive_tokens_activation": [ 14 ], "top_negative_tokens": [ "الحياه", "stateProvider", "Personendaten" ], "top_negative_tokens_contribution": [ -34.25, -33.75, -33.5 ], "top_negative_tokens_ids": [ 113904, 196575, 230304 ], "top_negative_tokens_relative_con...	{ "top_negative_tokens": [], "top_positive_tokens": [ " " ] }	[]	0.000021	1,753,088	[ " winter" ]	[ " winter" ]	true	1
{ "feature_idx": 20, "layer": 0 }	{ "positive_tokens_activation": [ 8.75, 10.25, 10.9375, 9.4375 ], "top_negative_tokens": [], "top_negative_tokens_contribution": [], "top_negative_tokens_ids": [], "top_negative_tokens_relative_contribution": [], "top_positive_token_ids": [ 14403, 17791, 1137, 20540 ], ...	{ "top_negative_tokens": [], "top_positive_tokens": [ " fieldNum", "EDEFAULT" ] }	[]	0.000049	2,113,536	[ " hardly", " inventory", " ourselves", "ins" ]	[ " hardly", " inventory", " ourselves", "ins" ]	true	1
{ "feature_idx": 21, "layer": 0 }	{ "positive_tokens_activation": [ 1.0625, 0 ], "top_negative_tokens": [ "TargetException", "canestro", "醐" ], "top_negative_tokens_contribution": [ -43, -41.25, -40.75 ], "top_negative_tokens_ids": [ 177901, 234875, 243512 ], "top_negative_tokens_relative_co...	{ "top_negative_tokens": [ "<bos>" ], "top_positive_tokens": [ "programme", " الحره" ] }	[]	0.000019	2,375,680	[ " “" ]	[ " “" ]	true	1
{ "feature_idx": 22, "layer": 0 }	{ "positive_tokens_activation": [ 11.3125, 9, 9.8125, 7.875, 7.625 ], "top_negative_tokens": [ "WEBPACK" ], "top_negative_tokens_contribution": [ -30.625 ], "top_negative_tokens_ids": [ 40122 ], "top_negative_tokens_relative_contribution": [ 0.00001707033516140654 ...	{ "top_negative_tokens": [ " myſelf", " Monfieur" ], "top_positive_tokens": [ " " ] }	[]	0.000072	1,794,048	[ " formed", " forming", "ality", "ios", "mos" ]	[ " formed", " forming", "ality", "ios", "mos" ]	true	1
{ "feature_idx": 23, "layer": 0 }	{ "positive_tokens_activation": [ 11.3125, 6.8125, 7.4375, 6.6875, 3.75, 6.0625 ], "top_negative_tokens": [ "FormTagHelper", "IsContent", "SequentialGroup" ], "top_negative_tokens_contribution": [ -59.75, -58.25, -57.75 ], "top_negative_tokens_ids": [ 11...	{ "top_negative_tokens": [ " specie" ], "top_positive_tokens": [ "<bos>", " MainAxisSize" ] }	[]	0.00006	2,719,744	[ " Cream", " President", " cream", " whom", "President", "cream" ]	[ " Cream", " President", " cream", " whom", "President", "cream" ]	true	1
{ "feature_idx": 24, "layer": 0 }	{ "positive_tokens_activation": [ 5.84375, 4.78125 ], "top_negative_tokens": [ " InputDecoration", "RegistryLite" ], "top_negative_tokens_contribution": [ -35, -34.25 ], "top_negative_tokens_ids": [ 115269, 143572 ], "top_negative_tokens_relative_contribution": [ 0....	{ "top_negative_tokens": [ "<bos>", "'", "\n\n" ], "top_positive_tokens": [ "tvguidetime", " HasFactory" ] }	[]	0.00003	1,474,560	[ " accused", " saw" ]	[ " accused", " saw" ]	true	1
{ "feature_idx": 25, "layer": 0 }	{ "positive_tokens_activation": [ 0, 2.296875, 1.515625 ], "top_negative_tokens": [ "Personendaten", "webElementXpaths", " autorytatywna" ], "top_negative_tokens_contribution": [ -44.25, -40.75, -40.25 ], "top_negative_tokens_ids": [ 230304, 73606, 84694 ]...	{ "top_negative_tokens": [ " مرئيه" ], "top_positive_tokens": [ "\n\n", "\n" ] }	[]	0.000013	2,523,136	[ " berkata", "mentaux" ]	[ " berkata", "mentaux" ]	true	1
{ "feature_idx": 26, "layer": 0 }	{ "positive_tokens_activation": [ 12.6875, 10.3125, 9.5 ], "top_negative_tokens": [ "GenerationType", "Бахар", " Савезне" ], "top_negative_tokens_contribution": [ -43, -37.5, -34.25 ], "top_negative_tokens_ids": [ 114531, 199141, 146734 ], "top_negative_...	{ "top_negative_tokens": [ "setVerticalGroup", "tvguidetime", "NUMX", "AutoresizingMask" ], "top_positive_tokens": [ " same", " to" ] }	[]	0.000046	2,007,040	[ " late", " owned", " private" ]	[ " late", " owned", " private" ]	true	1
{ "feature_idx": 27, "layer": 0 }	{ "positive_tokens_activation": [ 3.03125, 2.6875 ], "top_negative_tokens": [ "\u0004", "__[\"", "DockStyle", "ChildScrollView" ], "top_negative_tokens_contribution": [ -24.375, -23.5, -23.25, -21.5 ], "top_negative_tokens_ids": [ 250124, 52765, 124466, ...	{ "top_negative_tokens": [], "top_positive_tokens": [ "WebServlet", "forName" ] }	[]	0.000041	831,488	[ " useHistory", "נטרנט" ]	[ " useHistory", "נטרנט" ]	true	1
{ "feature_idx": 28, "layer": 0 }	{ "positive_tokens_activation": [ 18.125, 15.625, 15, 14.625, 14.625 ], "top_negative_tokens": [ "RenderAtEndOf", "GEBURTSDATUM", " صوتيه", "BeginContext" ], "top_negative_tokens_contribution": [ -52.75, -43.75, -41.5, -40.5 ], "top_negative_tokens_ids":...	{ "top_negative_tokens": [ "出版年" ], "top_positive_tokens": [ "<bos>", "\n", "'" ] }	[]	0.00009	2,146,304	[ " Segment", " linked", " segment", " segments", "segment" ]	[ " Segment", " linked", " segment", " segments", "segment" ]	true	1
{ "feature_idx": 29, "layer": 0 }	{ "positive_tokens_activation": [ 12.0625, 14.1875, 10.8125, 10.5625 ], "top_negative_tokens": [ " autorytatywna", "fjspx" ], "top_negative_tokens_contribution": [ -37.25, -33.25 ], "top_negative_tokens_ids": [ 84694, 217589 ], "top_negative_tokens_relative_cont...	{ "top_negative_tokens": [], "top_positive_tokens": [ "\n\n", "\n" ] }	[]	0.00007	1,884,160	[ "\f", " bond", " dog", " drain" ]	[ "\f", " bond", " dog", " drain" ]	true	1
{ "feature_idx": 30, "layer": 0 }	{ "positive_tokens_activation": [ 13.625, 14.125, 11, 11, 10.625, 11.125, 9.375, 11.5 ], "top_negative_tokens": [ " autorytatywna", " ivelany", "Rhestr", "Jeografia", "Попис" ], "top_negative_tokens_contribution": [ -48, -38.75, -37, -37, ...	{ "top_negative_tokens": [], "top_positive_tokens": [ "i", "o", "a", " the" ] }	[]	0.000119	2,088,960	[ " Summer", " competitive", " feature", " summer", " whose", "Summer", "feature", "summer" ]	[ " Summer", " competitive", " feature", " summer", " whose", "Summer", "feature", "summer" ]	true	1
{ "feature_idx": 31, "layer": 0 }	{ "positive_tokens_activation": [ 20.125, 18.75, 17.875, 15.75, 17.375, 16.125, 16.5 ], "top_negative_tokens": [ "SequentialGroup", " Finlande" ], "top_negative_tokens_contribution": [ -33.75, -33.5 ], "top_negative_tokens_ids": [ 46666, 221496 ], "t...	{ "top_negative_tokens": [ "<bos>", "’" ], "top_positive_tokens": [ " Reſ" ] }	[]	0.000127	2,146,304	[ " Pour", " pour", " poured", " pouring", " pours", "Pour", "pour" ]	[ " Pour", " pour", " poured", " pouring", " pours", "Pour", "pour" ]	true	1
{ "feature_idx": 32, "layer": 0 }	{ "positive_tokens_activation": [ 12.625, 11.75, 9.5625, 7.0625, 6, 7.0625 ], "top_negative_tokens": [ "RenderAtEndOf" ], "top_negative_tokens_contribution": [ -46.25 ], "top_negative_tokens_ids": [ 234397 ], "top_negative_tokens_relative_contribution": [ 0.0000...	{ "top_negative_tokens": [ "\n\n" ], "top_positive_tokens": [] }	[]	0.00006	2,342,912	[ " Prefer", " better", " dollar", " prefer", " wanna", "{{" ]	[ " Prefer", " better", " dollar", " prefer", " wanna", "{{" ]	true	1
{ "feature_idx": 33, "layer": 0 }	{ "positive_tokens_activation": [ 2.375 ], "top_negative_tokens": [ "ES" ], "top_negative_tokens_contribution": [ -8.625 ], "top_negative_tokens_ids": [ 988 ], "top_negative_tokens_relative_contribution": [ 0.00001595236972207203 ], "top_positive_token_ids": [ 220758 ], ...	{ "top_negative_tokens": [ "\n\n" ], "top_positive_tokens": [ "ագրություններ", " FetchType", " resourceCulture" ] }	[]	0.000027	540,672	[ " Theſe" ]	[ " Theſe" ]	true	1
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{ "feature_idx": 77, "layer": 0 }	{ "positive_tokens_activation": [], "top_negative_tokens": [ " needed", "’" ], "top_negative_tokens_contribution": [ -14.0625, -13.0625 ], "top_negative_tokens_ids": [ 4880, 235349 ], "top_negative_tokens_relative_contribution": [ 0.00002007735383813269, 0.000018649630874...	{ "top_negative_tokens": [], "top_positive_tokens": [ " resourceCulture" ] }	[]	0	700,416	null	null	false	0
{ "feature_idx": 78, "layer": 0 }	{ "positive_tokens_activation": [ 13.5, 7.53125, 7.46875, 3.84375 ], "top_negative_tokens": [ " صوتيه", "Personensuche" ], "top_negative_tokens_contribution": [ -51.75, -51.5 ], "top_negative_tokens_ids": [ 204197, 121159 ], "top_negative_tokens_relative_contrib...	{ "top_negative_tokens": [], "top_positive_tokens": [ "\n\n", ",", "\n" ] }	[]	0.000038	2,588,672	[ " Si", " positions", " si", "Si" ]	[ " Si", " positions", " si", "Si" ]	true	1
{ "feature_idx": 79, "layer": 0 }	{ "positive_tokens_activation": [ 12.375, 12.25 ], "top_negative_tokens": [ " AssemblyVersion", "migrationBuilder", "addGap" ], "top_negative_tokens_contribution": [ -37.25, -37, -36.75 ], "top_negative_tokens_ids": [ 66562, 43223, 31659 ], "top_negative_tok...	{ "top_negative_tokens": [ "<bos>", " feroit" ], "top_positive_tokens": [ "\n\n", " \"", " '", "\n", "'", " ", "{" ] }	[]	0.000034	1,712,128	[ " publisher", " publishing" ]	[ " publisher", " publishing" ]	true	1
{ "feature_idx": 80, "layer": 0 }	{ "positive_tokens_activation": [ 2.640625 ], "top_negative_tokens": [ "IntoConstraints", "AndEndTag" ], "top_negative_tokens_contribution": [ -19.625, -18.625 ], "top_negative_tokens_ids": [ 211076, 174788 ], "top_negative_tokens_relative_contribution": [ 0.00002886301...	{ "top_negative_tokens": [], "top_positive_tokens": [ " de", " De" ] }	[]	0.000029	679,936	[ " traditionnels" ]	[ " traditionnels" ]	true	1
{ "feature_idx": 81, "layer": 0 }	{ "positive_tokens_activation": [], "top_negative_tokens": [], "top_negative_tokens_contribution": [], "top_negative_tokens_ids": [], "top_negative_tokens_relative_contribution": [], "top_positive_token_ids": [], "top_positive_tokens": [], "top_positive_tokens_contribution": [], "top_positive_tokens_r...	{ "top_negative_tokens": [ "MigrationBuilder", "########.", "<bos>", "sizeCache" ], "top_positive_tokens": [ " purposes", " process" ] }	[]	0	675,840	null	null	false	0
{ "feature_idx": 82, "layer": 0 }	{ "positive_tokens_activation": [ 16, 12.125, 12, 11.5, 11.5, 8 ], "top_negative_tokens": [ "rungsseite", "HasForeignKey" ], "top_negative_tokens_contribution": [ -38.5, -34.25 ], "top_negative_tokens_ids": [ 68479, 137209 ], "top_negative_tokens_relativ...	{ "top_negative_tokens": [ " and", " or", " (" ], "top_positive_tokens": [] }	[]	0.000096	1,941,504	[ " Housing", " housing", " residential", " supported", "Housing", "housing" ]	[ " Housing", " housing", " residential", " supported", "Housing", "housing" ]	true	1
{ "feature_idx": 83, "layer": 0 }	{ "positive_tokens_activation": [], "top_negative_tokens": [ " وتسجيلات", " beginnetje", " BrowserModule" ], "top_negative_tokens_contribution": [ -38.5, -37, -32.75 ], "top_negative_tokens_ids": [ 208221, 149366, 186886 ], "top_negative_tokens_relative_contribution":...	{ "top_negative_tokens": [ "_", " _" ], "top_positive_tokens": [ "<bos>", " itſelf", " Efq" ] }	[]	0	1,933,312	null	null	false	0
{ "feature_idx": 84, "layer": 0 }	{ "positive_tokens_activation": [ 9.8125, 7.1875, 9.1875, 8.75 ], "top_negative_tokens": [ "ISupport", "unknownFields", " nakalista" ], "top_negative_tokens_contribution": [ -37.25, -36.75, -35 ], "top_negative_tokens_ids": [ 58566, 74779, 203832 ], ...	{ "top_negative_tokens": [ "issauga" ], "top_positive_tokens": [ "<bos>", "Personensuche" ] }	[]	0.00006	1,867,776	[ " degree", " themselves", " transaction", " trip" ]	[ " degree", " themselves", " transaction", " trip" ]	true	1
{ "feature_idx": 85, "layer": 0 }	{ "positive_tokens_activation": [ 0.8125, 0, 1.84375 ], "top_negative_tokens": [ "apimachinery", "RegressionTest", "ราบ" ], "top_negative_tokens_contribution": [ -19, -18.625, -18 ], "top_negative_tokens_ids": [ 165038, 157911, 207493 ], "top_negative_to...	{ "top_negative_tokens": [ "tagHelperRunner" ], "top_positive_tokens": [ "<bos>" ] }	[]	0.000032	966,656	[ " ویکی‌پدیا", "arschu" ]	[ " ویکی‌پدیا", "arschu" ]	true	1
{ "feature_idx": 86, "layer": 0 }	{ "positive_tokens_activation": [ 4.1875 ], "top_negative_tokens": [ "XmlAccessType" ], "top_negative_tokens_contribution": [ -28.5 ], "top_negative_tokens_ids": [ 113869 ], "top_negative_tokens_relative_contribution": [ 0.000025770399588509466 ], "top_positive_token_ids": [ ...	{ "top_negative_tokens": [ " Jefus", " Efq" ], "top_positive_tokens": [ "," ] }	[]	0.000012	1,105,920	[ " neither" ]	[ " neither" ]	true	1
{ "feature_idx": 87, "layer": 0 }	{ "positive_tokens_activation": [ 12.75, 11.875, 12 ], "top_negative_tokens": [ "DataAnnotations" ], "top_negative_tokens_contribution": [ -34.25 ], "top_negative_tokens_ids": [ 77215 ], "top_negative_tokens_relative_contribution": [ 0.00001891813735710457 ], "top_posit...	{ "top_negative_tokens": [ "^(@)", ".”—" ], "top_positive_tokens": [ " noDo", "Portály", " In" ] }	[]	0.000052	1,810,432	[ " Introduction", " introduction", "introduction" ]	[ " Introduction", " introduction", "introduction" ]	true	1
{ "feature_idx": 88, "layer": 0 }	{ "positive_tokens_activation": [], "top_negative_tokens": [ "出版年" ], "top_negative_tokens_contribution": [ -16.375 ], "top_negative_tokens_ids": [ 151160 ], "top_negative_tokens_relative_contribution": [ 0.00001776801218511536 ], "top_positive_token_ids": [], "top_positive_tokens"...	{ "top_negative_tokens": [], "top_positive_tokens": [ "<bos>" ] }	[]	0	921,600	null	null	false	0
{ "feature_idx": 89, "layer": 0 }	{ "positive_tokens_activation": [ 9.75, 8.125, 7.15625, 7.34375 ], "top_negative_tokens": [ "rungsseite", "SOUNDBITE", "RenderAtEndOf", "Datuak" ], "top_negative_tokens_contribution": [ -43.5, -38.75, -38.25, -37.75 ], "top_negative_tokens_ids": [ 68479,...	{ "top_negative_tokens": [ "<bos>", "/*", "IntoConstraints", "//" ], "top_positive_tokens": [ "fully", "ally", "ically" ] }	[]	0.000058	1,867,776	[ " OBITUARY", " cash", "\\]", "{~" ]	[ " OBITUARY", " cash", "\\]", "{~" ]	true	1
{ "feature_idx": 90, "layer": 0 }	{ "positive_tokens_activation": [], "top_negative_tokens": [ "isContained", "visející" ], "top_negative_tokens_contribution": [ -28.875, -28.5 ], "top_negative_tokens_ids": [ 185483, 145477 ], "top_negative_tokens_relative_contribution": [ 0.000018950431694975123, 0.00001...	{ "top_negative_tokens": [ "<bos>" ], "top_positive_tokens": [ "RectangleBorder", "/******/" ] }	[]	0	1,523,712	null	null	false	0
{ "feature_idx": 91, "layer": 0 }	{ "positive_tokens_activation": [ 15.0625, 13.5625, 10.625, 9.875, 9.75, 9.6875 ], "top_negative_tokens": [ "UnusedPrivate", "DebuggerNonUser", "jsonwebtoken", "المناصب" ], "top_negative_tokens_contribution": [ -36, -35.25, -34.5, -34.5 ], "top_negat...	{ "top_negative_tokens": [], "top_positive_tokens": [ "addGap" ] }	[]	0.000095	1,925,120	[ " bra", " catalog", " logic", " personnel", " sudden", "bra" ]	[ " bra", " catalog", " logic", " personnel", " sudden", "bra" ]	true	1
{ "feature_idx": 92, "layer": 0 }	{ "positive_tokens_activation": [ 11.375, 9.875, 9.625, 9.125, 9.875, 7.90625 ], "top_negative_tokens": [ "prefixer" ], "top_negative_tokens_contribution": [ -33.25 ], "top_negative_tokens_ids": [ 229383 ], "top_negative_tokens_relative_contribution": [ 0.000017...	{ "top_negative_tokens": [ " متعلقه", "IsMutable" ], "top_positive_tokens": [ "<bos>", "’", "'" ] }	[]	0.00009	1,908,736	[ " Book", " Books", " book", " books", "book", "books" ]	[ " Book", " Books", " book", " books", "book", "books" ]	true	1
{ "feature_idx": 93, "layer": 0 }	{ "positive_tokens_activation": [ 10.5, 6.5 ], "top_negative_tokens": [ "+#+#", "rungsseite", "MigrationBuilder", " ModelExpression", "GEBURTSDATUM", "ChildScrollView" ], "top_negative_tokens_contribution": [ -49, -48, -47.25, -43.5, -42, -41.75 ], "...	{ "top_negative_tokens": [ " key", " important" ], "top_positive_tokens": [ "<bos>" ] }	[]	0.000036	1,957,888	[ " key", "key" ]	[ " key", "key" ]	true	1
{ "feature_idx": 94, "layer": 0 }	{ "positive_tokens_activation": [ 15.625, 12.375, 11.875, 11.375, 10 ], "top_negative_tokens": [ "HostException", "Abitanti" ], "top_negative_tokens_contribution": [ -36.75, -36 ], "top_negative_tokens_ids": [ 199731, 164880 ], "top_negative_tokens_relative_...	{ "top_negative_tokens": [ " enfans" ], "top_positive_tokens": [ "endphp" ] }	[]	0.000094	1,720,320	[ " Extension", " extended", " extension", " extensions", "extension" ]	[ " Extension", " extended", " extension", " extensions", "extension" ]	true	1
{ "feature_idx": 95, "layer": 0 }	{ "positive_tokens_activation": [ 1, 1.09375, 1.78125, 1.28125, 0.7187500000000001 ], "top_negative_tokens": [ " but", " is" ], "top_negative_tokens_contribution": [ -17.625, -16.75 ], "top_negative_tokens_ids": [ 901, 603 ], "top_negative_tokens_relative_co...	{ "top_negative_tokens": [ "\n\n", " ", "." ], "top_positive_tokens": [ " itſelf" ] }	[]	0.000082	782,336	[ " BoxFit", " MotionEvent", " jScrollPane", "IntoConstraints", "initComponents" ]	[ " BoxFit", " MotionEvent", " jScrollPane", "IntoConstraints", "initComponents" ]	true	1
{ "feature_idx": 96, "layer": 0 }	{ "positive_tokens_activation": [ 4.21875 ], "top_negative_tokens": [ " autorytatywna", "lorette" ], "top_negative_tokens_contribution": [ -40.5, -34.5 ], "top_negative_tokens_ids": [ 84694, 160520 ], "top_negative_tokens_relative_contribution": [ 0.00001886964673758484...	{ "top_negative_tokens": [ "tvguidetime", " متعلقه" ], "top_positive_tokens": [ "<bos>", "'", "\n", "\n\n", "’", " " ] }	[]	0.000006	2,146,304	[ "конец" ]	[ "конец" ]	true	1
{ "feature_idx": 97, "layer": 0 }	{ "positive_tokens_activation": [ 7.46875, 9.25, 6.96875 ], "top_negative_tokens": [ " ivelany", " ModelExpression" ], "top_negative_tokens_contribution": [ -43.5, -41.25 ], "top_negative_tokens_ids": [ 195329, 152539 ], "top_negative_tokens_relative_contribution": ...	{ "top_negative_tokens": [ " ", " '", "<eos>" ], "top_positive_tokens": [ " feroit" ] }	[]	0.000041	1,769,472	[ " AS", "About", "quot" ]	[ " AS", "About", "quot" ]	true	1
{ "feature_idx": 98, "layer": 0 }	{ "positive_tokens_activation": [], "top_negative_tokens": [], "top_negative_tokens_contribution": [], "top_negative_tokens_ids": [], "top_negative_tokens_relative_contribution": [], "top_positive_token_ids": [], "top_positive_tokens": [], "top_positive_tokens_contribution": [], "top_positive_tokens_r...	{ "top_negative_tokens": [ " stage", "\u0012" ], "top_positive_tokens": [ "<bos>" ] }	[]	0	839,680	null	null	false	0
{ "feature_idx": 99, "layer": 0 }	{ "positive_tokens_activation": [ 13.5625, 11.8125, 13.4375, 11.0625, 11.8125 ], "top_negative_tokens": [ "argout" ], "top_negative_tokens_contribution": [ -39.25 ], "top_negative_tokens_ids": [ 163830 ], "top_negative_tokens_relative_contribution": [ 0.000017614926...	{ "top_negative_tokens": [ "ⓘ", "subsubsection" ], "top_positive_tokens": [ "MigrationBuilder" ] }	[]	0.000075	2,228,224	[ " crown", " inclusion", " plant", " plants", " provision" ]	[ " crown", " inclusion", " plant", " plants", " provision" ]	true	1

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CircuitLens & WeightLens: Transcoder Descriptions and Evaluations

This dataset contains automatically generated descriptions and evaluation metrics for Gemma-2-2B transcoders, produced using CircuitLens and WeightLens methods.

Methods

CircuitLens: https://github.com/egolimblevskaia/CircuitLens
WeightLens: https://github.com/egolimblevskaia/WeightLens

Dataset Structure

The dataset is organized by layers (0, 4, 7, 10, 12, 15, 18, 21, 23, 25), with each layer containing CSV files for different description methods:

├── layer_0/
│   ├── WeightLens.csv
│   ├── WeightLens_Out.csv
│   ├── WeightLens_Out_LLM.csv
│   ├── CircuitLens-Input.csv
│   ├── CircuitLens-Full.csv
│   ├── CircuitLens-Input_top.csv
│   ├── CircuitLens-Full_top.csv
│   ├── WL_CircuitLens-Full.csv
│   ├── Neuronpedia.csv
│   └── MaxAct.csv
├── layer_4/
│   └── ...
└── ...

CSV Columns

Column	Description
`neuron_idx`	Transcoder neuron index
`description`	Generated concept description
`Clarity`	Clarity evaluation metric
`Responsiveness`	Responsiveness evaluation metric
`Purity`	Purity evaluation metric
`Faithfulness`	Faithfulness evaluation metric

Paper

Circuit Insights: Towards Interpretability Beyond Activations

Elena Golimblevskaia, Aakriti Jain, Bruno Puri, Ammar Ibrahim, Wojciech Samek, and Sebastian Lapuschkin

https://arxiv.org/abs/2510.14936

Citation

@misc{golimblevskaia2025circuitinsightsinterpretabilityactivations,
      title={Circuit Insights: Towards Interpretability Beyond Activations}, 
      author={Elena Golimblevskaia and Aakriti Jain and Bruno Puri and Ammar Ibrahim and Wojciech Samek and Sebastian Lapuschkin},
      year={2025},
      eprint={2510.14936},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2510.14936}, 
}

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Paper for egolimblevskaia/weightlens-gemma-2-2b-transcoder-descriptions

Circuit Insights: Towards Interpretability Beyond Activations

Paper • 2510.14936 • Published Oct 16, 2025