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llmdbg

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train

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

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
format_version: int64
artifact: string
sha256: string
model_id: string
compatible_models: list<item: null>
  child 0, item: null
model_revision: null
method: string
method_version: int64
hidden_size: int64
layers: list<item: int64>
  child 0, item: int64
target_layer: int64
dtype: string
dataset: string
prompts: int64
max_seq_len: int64
skip_first: int64
rules: struct<ln_rule: bool, identity_rule: bool, half_rule: bool>
  child 0, ln_rule: bool
  child 1, identity_rule: bool
  child 2, half_rule: bool
r_lenses: list<item: struct<model_id: string, compatible_models: list<item: string>, method: string, version:  (... 164 chars omitted)
  child 0, item: struct<model_id: string, compatible_models: list<item: string>, method: string, version: int64, path (... 152 chars omitted)
      child 0, model_id: string
      child 1, compatible_models: list<item: string>
          child 0, item: string
      child 2, method: string
      child 3, version: int64
      child 4, path: string
      child 5, source_repo_id: string
      child 6, source_repo_type: string
      child 7, source_revision: string
      child 8, source_filename: string
      child 9, source_size: int64
      child 10, source_sha256: string
j_lenses: list<item: struct<model_id: string, compatible_models: list<item: string>, method: string, version:  (... 164 chars omitted)
  child 0, item: struct<model_id: string, compatible_models: list<item: string>, method: string, version: int64, path (... 152 chars omitted)
      child 0, model_id: string
      child 1, compatible_models: list<item: string>
          child 0, item: string
      child 2, method: string
      child 3, version: int64
      child 4, path: string
      child 5, source_repo_id: string
      child 6, source_repo_type: string
      child 7, source_revision: string
      child 8, source_filename: string
      child 9, source_size: int64
      child 10, source_sha256: string
to
{'format_version': Value('int64'), 'j_lenses': List({'model_id': Value('string'), 'compatible_models': List(Value('string')), 'method': Value('string'), 'version': Value('int64'), 'path': Value('string'), 'source_repo_id': Value('string'), 'source_repo_type': Value('string'), 'source_revision': Value('string'), 'source_filename': Value('string'), 'source_size': Value('int64'), 'source_sha256': Value('string')}), 'r_lenses': List({'model_id': Value('string'), 'compatible_models': List(Value('string')), 'method': Value('string'), 'version': Value('int64'), 'path': Value('string'), 'source_repo_id': Value('string'), 'source_repo_type': Value('string'), 'source_revision': Value('string'), 'source_filename': Value('string'), 'source_size': Value('int64'), 'source_sha256': Value('string')})}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, 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 127, 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 483, 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 2951, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, 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 547, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, 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 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              format_version: int64
              artifact: string
              sha256: string
              model_id: string
              compatible_models: list<item: null>
                child 0, item: null
              model_revision: null
              method: string
              method_version: int64
              hidden_size: int64
              layers: list<item: int64>
                child 0, item: int64
              target_layer: int64
              dtype: string
              dataset: string
              prompts: int64
              max_seq_len: int64
              skip_first: int64
              rules: struct<ln_rule: bool, identity_rule: bool, half_rule: bool>
                child 0, ln_rule: bool
                child 1, identity_rule: bool
                child 2, half_rule: bool
              r_lenses: list<item: struct<model_id: string, compatible_models: list<item: string>, method: string, version:  (... 164 chars omitted)
                child 0, item: struct<model_id: string, compatible_models: list<item: string>, method: string, version: int64, path (... 152 chars omitted)
                    child 0, model_id: string
                    child 1, compatible_models: list<item: string>
                        child 0, item: string
                    child 2, method: string
                    child 3, version: int64
                    child 4, path: string
                    child 5, source_repo_id: string
                    child 6, source_repo_type: string
                    child 7, source_revision: string
                    child 8, source_filename: string
                    child 9, source_size: int64
                    child 10, source_sha256: string
              j_lenses: list<item: struct<model_id: string, compatible_models: list<item: string>, method: string, version:  (... 164 chars omitted)
                child 0, item: struct<model_id: string, compatible_models: list<item: string>, method: string, version: int64, path (... 152 chars omitted)
                    child 0, model_id: string
                    child 1, compatible_models: list<item: string>
                        child 0, item: string
                    child 2, method: string
                    child 3, version: int64
                    child 4, path: string
                    child 5, source_repo_id: string
                    child 6, source_repo_type: string
                    child 7, source_revision: string
                    child 8, source_filename: string
                    child 9, source_size: int64
                    child 10, source_sha256: string
              to
              {'format_version': Value('int64'), 'j_lenses': List({'model_id': Value('string'), 'compatible_models': List(Value('string')), 'method': Value('string'), 'version': Value('int64'), 'path': Value('string'), 'source_repo_id': Value('string'), 'source_repo_type': Value('string'), 'source_revision': Value('string'), 'source_filename': Value('string'), 'source_size': Value('int64'), 'source_sha256': Value('string')}), 'r_lenses': List({'model_id': Value('string'), 'compatible_models': List(Value('string')), 'method': Value('string'), 'version': Value('int64'), 'path': Value('string'), 'source_repo_id': Value('string'), 'source_repo_type': Value('string'), 'source_revision': Value('string'), 'source_filename': Value('string'), 'source_size': Value('int64'), 'source_sha256': Value('string')})}
              because column names don't match

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llmdbg analysis artifacts

Versioned analysis data used by llmdbg.

Method references:

J-Lens

J-Lens artifacts contain averaged ordinary Jacobians from each residual layer to the final residual layer. They are fitted with Anthropic's reference jacobian-lens implementation, without the RelP backward-rule substitutions used for R-Lens.

R-Lens

R-Lens artifacts contain a learned residual-transport matrix for each source layer. Neuron Lens applies the appropriate transport to an MLP neuron's output direction, then applies the target model's final normalization and unembedding.

Each artifact directory contains:

manifest.json: model compatibility, fitting provenance, tensor metadata, and SHA-256 integrity information.
lens.safetensors: matrices named J.0, J.1, and so on.

The catalog includes locally fitted 0.8B and 2B Base maps. Their manifests explicitly allow compatible use with the corresponding Instruct checkpoints. That Base-to-Instruct reuse is a convenience approximation; an artifact fitted on the exact checkpoint is preferred for rigorous analysis.

The Qwen3.5 9B and 27B entries reference checkpoint-matched J-Lens and R-Lens maps from the R-Lens authors' pinned workspace-lenses release. The catalog records the immutable revision, file size, and SHA-256; llmdbg verifies the downloaded file before loading it. This avoids duplicating roughly 8.7 GB while keeping artifact resolution reproducible.

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Total file size:

532 MB