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The dataset generation failed because of a cast error
Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 58 new columns ({'max_persistence_h1', 'mean_death_h1', 'q3_birth_h2', 'q1_persistence_h2', 'q1_birth_h2', 'min_death_h2', 'median_birth_h1', 'bar_count_h0', 'q3_persistence_h1', 'persistent_entropy_h2', 'min_persistence_h2', 'std_death_h2', 'q3_death_h0', 'std_persistence_h1', 'min_persistence_h1', 'q3_persistence_h2', 'mean_birth_h1', 'total_persistence_h0', 'bar_count_h2', 'min_death_h0', 'median_death_h2', 'min_birth_h1', 'total_persistence_h1', 'mean_birth_h2', 'mean_persistence_h2', 'q1_death_h1', 'mean_persistence_h1', 'median_birth_h2', 'std_death_h0', 'std_death_h1', 'std_persistence_h2', 'std_birth_h2', 'min_death_h1', 'max_death_h2', 'q1_death_h0', 'persistent_entropy_h1', 'mean_death_h0', 'median_death_h0', 'std_birth_h1', 'q1_persistence_h1', 'median_persistence_h2', 'total_persistence_h2', 'min_birth_h2', 'q3_death_h2', 'mean_death_h2', 'persistent_entropy_h0', 'q3_birth_h1', 'bar_count_h1', 'max_birth_h1', 'q1_birth_h1', 'median_persistence_h1', 'max_birth_h2', 'q3_death_h1', 'q1_death_h2', 'max_persistence_h2', 'max_death_h1', 'median_death_h1', 'max_death_h0'}) and 9 missing columns ({'subject', 'revision', 'corpus', 'layer', 'head', 'n_points', 'step', 'n_prompts', 'vector_dim'}).

This happened while the csv dataset builder was generating data using

hf://datasets/sveneziale/activations-and-barcodes/barcodes/pythia-160m/pile2048_seed1/attn_out/persistence/cosine/persistence_summaries.csv (at revision df5c8805ac6fca09e07f02720f669995c1b1aeb3), ['hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/activations/pythia-160m/pile2048_seed1/attn_out/activation_metadata.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/activations/pythia-160m/pile2048_seed1/mlp_out/activation_metadata.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/activations/pythia-160m/pile2048_seed1/resid_post/activation_metadata.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/activations/pythia-160m/pile2048_seed2/attn_out/activation_metadata.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/activations/pythia-160m/pile2048_seed2/mlp_out/activation_metadata.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/activations/pythia-160m/pile2048_seed2/resid_post/activation_metadata.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/activations/pythia-70m/pile2048_seed1/attn_out/activation_metadata.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/activations/pythia-70m/pile2048_seed1/mlp_out/activation_metadata.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/activations/pythia-70m/pile2048_seed1/resid_post/activation_metadata.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/activations/pythia-70m/pile2048_seed2/attn_out/activation_metadata.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/activations/pythia-70m/pile2048_seed2/mlp_out/activation_metadata.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/activations/pythia-70m/pile2048_seed2/resid_post/activation_metadata.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-160m/pile2048_seed1/attn_out/persistence/cosine/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-160m/pile2048_seed1/attn_out/persistence/euclidean/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-160m/pile2048_seed1/mlp_out/persistence/cosine/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-160m/pile2048_seed1/mlp_out/persistence/euclidean/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-160m/pile2048_seed1/resid_post/persistence/cosine/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-160m/pile2048_seed1/resid_post/persistence/euclidean/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-160m/pile2048_seed2/attn_out/persistence/cosine/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-160m/pile2048_seed2/attn_out/persistence/euclidean/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-160m/pile2048_seed2/mlp_out/persistence/cosine/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-160m/pile2048_seed2/mlp_out/persistence/euclidean/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-160m/pile2048_seed2/resid_post/persistence/cosine/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-160m/pile2048_seed2/resid_post/persistence/euclidean/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-70m/pile2048_seed1/attn_out/persistence/cosine/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-70m/pile2048_seed1/attn_out/persistence/euclidean/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-70m/pile2048_seed1/mlp_out/persistence/cosine/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-70m/pile2048_seed1/mlp_out/persistence/euclidean/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-70m/pile2048_seed1/resid_post/persistence/cosine/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-70m/pile2048_seed1/resid_post/persistence/euclidean/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-70m/pile2048_seed2/attn_out/persistence/cosine/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-70m/pile2048_seed2/attn_out/persistence/euclidean/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-70m/pile2048_seed2/mlp_out/persistence/cosine/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-70m/pile2048_seed2/mlp_out/persistence/euclidean/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-70m/pile2048_seed2/resid_post/persistence/cosine/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-70m/pile2048_seed2/resid_post/persistence/euclidean/persistence_summaries.csv']

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1837, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 765, in write_table
                  self._write_table(pa_table, writer_batch_size=writer_batch_size)
                  ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              cloud_id: int64
              mean_death_h0: double
              min_death_h0: double
              q1_death_h0: double
              median_death_h0: double
              q3_death_h0: double
              max_death_h0: double
              std_death_h0: double
              total_persistence_h0: double
              bar_count_h0: double
              persistent_entropy_h0: double
              mean_birth_h1: double
              min_birth_h1: double
              q1_birth_h1: double
              median_birth_h1: double
              q3_birth_h1: double
              max_birth_h1: double
              std_birth_h1: double
              mean_death_h1: double
              min_death_h1: double
              q1_death_h1: double
              median_death_h1: double
              q3_death_h1: double
              max_death_h1: double
              std_death_h1: double
              mean_persistence_h1: double
              min_persistence_h1: double
              q1_persistence_h1: double
              median_persistence_h1: double
              q3_persistence_h1: double
              max_persistence_h1: double
              std_persistence_h1: double
              total_persistence_h1: double
              bar_count_h1: double
              persistent_entropy_h1: double
              mean_birth_h2: double
              min_birth_h2: double
              q1_birth_h2: double
              median_birth_h2: double
              q3_birth_h2: double
              max_birth_h2: double
              std_birth_h2: double
              mean_death_h2: double
              min_death_h2: double
              q1_death_h2: double
              median_death_h2: double
              q3_death_h2: double
              max_death_h2: double
              std_death_h2: double
              mean_persistence_h2: double
              min_persistence_h2: double
              q1_persistence_h2: double
              median_persistence_h2: double
              q3_persistence_h2: double
              max_persistence_h2: double
              std_persistence_h2: double
              total_persistence_h2: double
              bar_count_h2: double
              persistent_entropy_h2: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 7939
              to
              {'cloud_id': Value('int64'), 'revision': Value('string'), 'step': Value('int64'), 'corpus': Value('string'), 'layer': Value('int64'), 'head': Value('float64'), 'subject': Value('string'), 'n_prompts': Value('int64'), 'n_points': Value('int64'), 'vector_dim': Value('int64')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1683, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1839, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
                  ...<4 lines>...
                  )
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 58 new columns ({'max_persistence_h1', 'mean_death_h1', 'q3_birth_h2', 'q1_persistence_h2', 'q1_birth_h2', 'min_death_h2', 'median_birth_h1', 'bar_count_h0', 'q3_persistence_h1', 'persistent_entropy_h2', 'min_persistence_h2', 'std_death_h2', 'q3_death_h0', 'std_persistence_h1', 'min_persistence_h1', 'q3_persistence_h2', 'mean_birth_h1', 'total_persistence_h0', 'bar_count_h2', 'min_death_h0', 'median_death_h2', 'min_birth_h1', 'total_persistence_h1', 'mean_birth_h2', 'mean_persistence_h2', 'q1_death_h1', 'mean_persistence_h1', 'median_birth_h2', 'std_death_h0', 'std_death_h1', 'std_persistence_h2', 'std_birth_h2', 'min_death_h1', 'max_death_h2', 'q1_death_h0', 'persistent_entropy_h1', 'mean_death_h0', 'median_death_h0', 'std_birth_h1', 'q1_persistence_h1', 'median_persistence_h2', 'total_persistence_h2', 'min_birth_h2', 'q3_death_h2', 'mean_death_h2', 'persistent_entropy_h0', 'q3_birth_h1', 'bar_count_h1', 'max_birth_h1', 'q1_birth_h1', 'median_persistence_h1', 'max_birth_h2', 'q3_death_h1', 'q1_death_h2', 'max_persistence_h2', 'max_death_h1', 'median_death_h1', 'max_death_h0'}) and 9 missing columns ({'subject', 'revision', 'corpus', 'layer', 'head', 'n_points', 'step', 'n_prompts', 'vector_dim'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/sveneziale/activations-and-barcodes/barcodes/pythia-160m/pile2048_seed1/attn_out/persistence/cosine/persistence_summaries.csv (at revision df5c8805ac6fca09e07f02720f669995c1b1aeb3), ['hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/activations/pythia-160m/pile2048_seed1/attn_out/activation_metadata.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/activations/pythia-160m/pile2048_seed1/mlp_out/activation_metadata.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/activations/pythia-160m/pile2048_seed1/resid_post/activation_metadata.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/activations/pythia-160m/pile2048_seed2/attn_out/activation_metadata.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/activations/pythia-160m/pile2048_seed2/mlp_out/activation_metadata.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/activations/pythia-160m/pile2048_seed2/resid_post/activation_metadata.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/activations/pythia-70m/pile2048_seed1/attn_out/activation_metadata.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/activations/pythia-70m/pile2048_seed1/mlp_out/activation_metadata.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/activations/pythia-70m/pile2048_seed1/resid_post/activation_metadata.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/activations/pythia-70m/pile2048_seed2/attn_out/activation_metadata.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/activations/pythia-70m/pile2048_seed2/mlp_out/activation_metadata.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/activations/pythia-70m/pile2048_seed2/resid_post/activation_metadata.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-160m/pile2048_seed1/attn_out/persistence/cosine/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-160m/pile2048_seed1/attn_out/persistence/euclidean/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-160m/pile2048_seed1/mlp_out/persistence/cosine/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-160m/pile2048_seed1/mlp_out/persistence/euclidean/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-160m/pile2048_seed1/resid_post/persistence/cosine/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-160m/pile2048_seed1/resid_post/persistence/euclidean/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-160m/pile2048_seed2/attn_out/persistence/cosine/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-160m/pile2048_seed2/attn_out/persistence/euclidean/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-160m/pile2048_seed2/mlp_out/persistence/cosine/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-160m/pile2048_seed2/mlp_out/persistence/euclidean/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-160m/pile2048_seed2/resid_post/persistence/cosine/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-160m/pile2048_seed2/resid_post/persistence/euclidean/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-70m/pile2048_seed1/attn_out/persistence/cosine/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-70m/pile2048_seed1/attn_out/persistence/euclidean/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-70m/pile2048_seed1/mlp_out/persistence/cosine/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-70m/pile2048_seed1/mlp_out/persistence/euclidean/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-70m/pile2048_seed1/resid_post/persistence/cosine/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-70m/pile2048_seed1/resid_post/persistence/euclidean/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-70m/pile2048_seed2/attn_out/persistence/cosine/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-70m/pile2048_seed2/attn_out/persistence/euclidean/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-70m/pile2048_seed2/mlp_out/persistence/cosine/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-70m/pile2048_seed2/mlp_out/persistence/euclidean/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-70m/pile2048_seed2/resid_post/persistence/cosine/persistence_summaries.csv', 'hf://datasets/sveneziale/activations-and-barcodes@df5c8805ac6fca09e07f02720f669995c1b1aeb3/barcodes/pythia-70m/pile2048_seed2/resid_post/persistence/euclidean/persistence_summaries.csv']
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

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sveneziale/activations-and-barcodes

Compute artifacts pushed by tda-for-llms's Hugging-Face-backed pipeline (hf.enabled: true in experiment.yaml).

Layout

Two top-level folders:

activations/{model_slug}/{corpus}/{act_name}/

Raw per-cloud activation matrices extracted from the model. Independent of topology.metric — the same activations are reused across every metric or topology config that shares the same model + corpus + activation stream, so they are only ever GPU-extracted once.

  • activation_metadata.csv — one row per cloud (cloud_id, revision, layer, head, n_prompts, ...).
  • activations.npz — raw matrices, keyed act_{cloud_id} matching the cloud_id column above.

barcodes/{model_slug}/{corpus}/{act_name}/{persistence|zigzag}/{metric}/

Persistent-homology outputs computed from the activations above. One copy per topology metric/mode, since the barcode depends on it.

  • persistence_summaries.csv — one row per cloud, scalar topological feature summary.
  • persistence_diagrams.npz — raw barcodes, keyed cloud_{cloud_id}_h{dim}.
  • manifest.json — full run provenance (model, revisions, activation stream, corpus, topology parameters).
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