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siddharthmb
/

2026.TA.overlay_huge_graphs

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Split (1)

train

The dataset viewer is not available for this split.

Cannot load the dataset split (in streaming mode) to extract the first rows.

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
metadata: struct<slug: string, scan: string, transcoder_list: list<item: null>, prompt_tokens: list<item: stri (... 519 chars omitted)
  child 0, slug: string
  child 1, scan: string
  child 2, transcoder_list: list<item: null>
      child 0, item: null
  child 3, prompt_tokens: list<item: string>
      child 0, item: string
  child 4, prompt: string
  child 5, node_threshold: double
  child 6, schema_version: int64
  child 7, comparison: struct<base_slug: string, adapter_slug: string, base_scan: string, adapter_scan: string, base_featur (... 338 chars omitted)
      child 0, base_slug: string
      child 1, adapter_slug: string
      child 2, base_scan: string
      child 3, adapter_scan: string
      child 4, base_feature_scan: string
      child 5, adapter_feature_scan: string
      child 6, node_shapes: struct<base: string, adapter: string, shared: string>
          child 0, base: string
          child 1, adapter: string
          child 2, shared: string
      child 7, link_filter: struct<hide_direct_embedding_logit_links: bool, skipped_direct_embedding_logit_links: struct<base: i (... 22 chars omitted)
          child 0, hide_direct_embedding_logit_links: bool
          child 1, skipped_direct_embedding_logit_links: struct<base: int64, adapter: int64>
              child 0, base: int64
              child 1, adapter: int64
      child 8, node_counts: struct<base_features: int64, adapter_features: int64, error_nodes: int64>
          child 0, base_features: int64
       
...
d 1, scan: string
      child 2, transcoder_list: list<item: null>
          child 0, item: null
      child 3, prompt_tokens: list<item: string>
          child 0, item: string
      child 4, prompt: string
      child 5, node_threshold: double
      child 6, schema_version: int64
      child 7, comparison: struct<base_slug: string, adapter_slug: string, base_scan: string, adapter_scan: string, base_featur (... 250 chars omitted)
          child 0, base_slug: string
          child 1, adapter_slug: string
          child 2, base_scan: string
          child 3, adapter_scan: string
          child 4, base_feature_scan: string
          child 5, adapter_feature_scan: string
          child 6, node_shapes: struct<base: string, adapter: string, shared: string>
              child 0, base: string
              child 1, adapter: string
              child 2, shared: string
          child 7, link_filter: struct<hide_direct_embedding_logit_links: bool, skipped_direct_embedding_logit_links: struct<base: i (... 22 chars omitted)
              child 0, hide_direct_embedding_logit_links: bool
              child 1, skipped_direct_embedding_logit_links: struct<base: int64, adapter: int64>
                  child 0, base: int64
                  child 1, adapter: int64
      child 8, node_counts: struct<base_features: int64, adapter_features: int64, error_nodes: int64>
          child 0, base_features: int64
          child 1, adapter_features: int64
          child 2, error_nodes: int64
to
{'graphs': List({'slug': Value('string'), 'scan': Value('string'), 'transcoder_list': List(Value('null')), 'prompt_tokens': List(Value('string')), 'prompt': Value('string'), 'node_threshold': Value('float64'), 'schema_version': Value('int64'), 'comparison': {'base_slug': Value('string'), 'adapter_slug': Value('string'), 'base_scan': Value('string'), 'adapter_scan': Value('string'), 'base_feature_scan': Value('string'), 'adapter_feature_scan': Value('string'), 'node_shapes': {'base': Value('string'), 'adapter': Value('string'), 'shared': Value('string')}, 'link_filter': {'hide_direct_embedding_logit_links': Value('bool'), 'skipped_direct_embedding_logit_links': {'base': Value('int64'), 'adapter': Value('int64')}}}, 'node_counts': {'base_features': Value('int64'), 'adapter_features': Value('int64'), 'error_nodes': Value('int64')}})}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 489, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_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
              metadata: struct<slug: string, scan: string, transcoder_list: list<item: null>, prompt_tokens: list<item: stri (... 519 chars omitted)
                child 0, slug: string
                child 1, scan: string
                child 2, transcoder_list: list<item: null>
                    child 0, item: null
                child 3, prompt_tokens: list<item: string>
                    child 0, item: string
                child 4, prompt: string
                child 5, node_threshold: double
                child 6, schema_version: int64
                child 7, comparison: struct<base_slug: string, adapter_slug: string, base_scan: string, adapter_scan: string, base_featur (... 338 chars omitted)
                    child 0, base_slug: string
                    child 1, adapter_slug: string
                    child 2, base_scan: string
                    child 3, adapter_scan: string
                    child 4, base_feature_scan: string
                    child 5, adapter_feature_scan: string
                    child 6, node_shapes: struct<base: string, adapter: string, shared: string>
                        child 0, base: string
                        child 1, adapter: string
                        child 2, shared: string
                    child 7, link_filter: struct<hide_direct_embedding_logit_links: bool, skipped_direct_embedding_logit_links: struct<base: i (... 22 chars omitted)
                        child 0, hide_direct_embedding_logit_links: bool
                        child 1, skipped_direct_embedding_logit_links: struct<base: int64, adapter: int64>
                            child 0, base: int64
                            child 1, adapter: int64
                    child 8, node_counts: struct<base_features: int64, adapter_features: int64, error_nodes: int64>
                        child 0, base_features: int64
                     
              ...
              d 1, scan: string
                    child 2, transcoder_list: list<item: null>
                        child 0, item: null
                    child 3, prompt_tokens: list<item: string>
                        child 0, item: string
                    child 4, prompt: string
                    child 5, node_threshold: double
                    child 6, schema_version: int64
                    child 7, comparison: struct<base_slug: string, adapter_slug: string, base_scan: string, adapter_scan: string, base_featur (... 250 chars omitted)
                        child 0, base_slug: string
                        child 1, adapter_slug: string
                        child 2, base_scan: string
                        child 3, adapter_scan: string
                        child 4, base_feature_scan: string
                        child 5, adapter_feature_scan: string
                        child 6, node_shapes: struct<base: string, adapter: string, shared: string>
                            child 0, base: string
                            child 1, adapter: string
                            child 2, shared: string
                        child 7, link_filter: struct<hide_direct_embedding_logit_links: bool, skipped_direct_embedding_logit_links: struct<base: i (... 22 chars omitted)
                            child 0, hide_direct_embedding_logit_links: bool
                            child 1, skipped_direct_embedding_logit_links: struct<base: int64, adapter: int64>
                                child 0, base: int64
                                child 1, adapter: int64
                    child 8, node_counts: struct<base_features: int64, adapter_features: int64, error_nodes: int64>
                        child 0, base_features: int64
                        child 1, adapter_features: int64
                        child 2, error_nodes: int64
              to
              {'graphs': List({'slug': Value('string'), 'scan': Value('string'), 'transcoder_list': List(Value('null')), 'prompt_tokens': List(Value('string')), 'prompt': Value('string'), 'node_threshold': Value('float64'), 'schema_version': Value('int64'), 'comparison': {'base_slug': Value('string'), 'adapter_slug': Value('string'), 'base_scan': Value('string'), 'adapter_scan': Value('string'), 'base_feature_scan': Value('string'), 'adapter_feature_scan': Value('string'), 'node_shapes': {'base': Value('string'), 'adapter': Value('string'), 'shared': Value('string')}, 'link_filter': {'hide_direct_embedding_logit_links': Value('bool'), 'skipped_direct_embedding_logit_links': {'base': Value('int64'), 'adapter': Value('int64')}}}, 'node_counts': {'base_features': Value('int64'), 'adapter_features': Value('int64'), 'error_nodes': Value('int64')}})}
              because column names don't match

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2026.TA.overlay_huge_graphs

Base-vs-adapter overlay attribution graphs (circuit-tracer JSON) for google/gemma-2-2b, contrasting the base GemmaScope transcoders against the huge 16384-feature transcoder adapter over the 40-prompt comprehensive set.

base side — base GemmaScope transcoders (width_16k, average_l0_76); reconstruct the base MLP, so this side stays base-like.
adapter side — the trained huge adapter siddharthmb/2026.TA.gemma2_2b_huge_tc16384_decb_l1w0.0003_norm_sch_tarbb_lb2.0_ln1.0_dr500000_lr2e-04_bs8_sl (2× capacity; B200 warm-start, final eval KL 0.142 / top-1 86.35%), which bridges base→instruct, so this side is instruct-like.

Why this repo exists (the fix). The original overlay_huge graph was built with run_combined_attribution, which runs ONE model on the base backbone — its forward collapses to base, so its completion/logit nodes were the base model's predictions (e.g. Answer/\n — base echoing/continuing the prompt), not the instruct-bridging adapter's. This repo is the corrected rebuild with run_base_adapter_comparison (runs the real adapter model + overlays a separate base run), so the adapter side shows instruction-tuned completions (e.g. Paris p≈0.96). Full story: my_notes/07-09-26/07-15-26 hybrid graph instruct-completions bug.md.

overlay/ — 40 full base-vs-adapter overlay graphs (all node types).
overlay_compact/ — 40 compact overlays (error nodes stripped, base features capped) — the servable set.

Serve it

uv run --extra viz python -m analysis.attribution.serve_comparison_graphs \
  --graph_file_dir siddharthmb/2026.TA.overlay_huge_graphs:overlay --port 8048
# or the compact set:  ...:overlay_compact

Regenerate (corrected build)

uv run --extra viz python -m analysis.attribution.run_base_adapter_comparison \
  --adapter_checkpoint siddharthmb/2026.TA.gemma2_2b_huge_tc16384_decb_l1w0.0003_norm_sch_tarbb_lb2.0_ln1.0_dr500000_lr2e-04_bs8_sl \
  --base_model google/gemma-2-2b --gemmascope_width width_16k --gemmascope_l0 average_l0_76 \
  --base_feature_data_path siddharthmb/2026.TA.features_gemma-2-2b_gemmascope_width_16k_average_l0_76_ms100000_ml1024_tk1_hf83e96d574d2 \
  --feature_data_path siddharthmb/2026.TA.features_2026.TA.gemma2_2b_huge_tc16384_decb_l1w0.0003_norm_sch_tarbb_lb2_hff15229f5fe1 \
  --prompts analysis/attribution/prompts/comprehensive --prompt_format chat \
  --max_feature_nodes 2048 --max_n_logits 10 \
  --run_name overlay_huge_fixed --output_dir <out>

Built on a RunPod B200 (run_base_adapter_comparison, this session).

Inputs

Base model: google/gemma-2-2b; prompt tokenizer google/gemma-2-2b-it.
Huge adapter (adapter side): siddharthmb/2026.TA.gemma2_2b_huge_tc16384_decb_l1w0.0003_norm_sch_tarbb_lb2.0_ln1.0_dr500000_lr2e-04_bs8_sl. Training wandb: c7vfz8o0.
Base features: siddharthmb/2026.TA.features_gemma-2-2b_gemmascope_width_16k_average_l0_76_ms100000_ml1024_tk1_hf83e96d574d2.
Adapter features: siddharthmb/2026.TA.features_2026.TA.gemma2_2b_huge_tc16384_decb_l1w0.0003_norm_sch_tarbb_lb2_hff15229f5fe1.

Provenance

Superseded original (base completions, run_combined_attribution): local /nlp/scr/siddharth/transcoder-adapters/overlay_huge/graph.
Adapter training wandb: siddharth-stanford/sparse-adaptation/runs/c7vfz8o0.
The attribution build itself is not wandb-logged.

Downloads last month: 36

Total file size:

1.04 GB

2026.TA.overlay_huge_graphs

Contents

Serve it

Regenerate (corrected build)

Inputs

Provenance