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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
descriptor: struct<execution: struct<accumulator_dtype: string, attention_backend: string, batch_policy: struct< (... 1598 chars omitted)
  child 0, execution: struct<accumulator_dtype: string, attention_backend: string, batch_policy: struct<algorithm: string, (... 759 chars omitted)
      child 0, accumulator_dtype: string
      child 1, attention_backend: string
      child 2, batch_policy: struct<algorithm: string, max_sequences: int64, max_tokens: int64, window_size: int64>
          child 0, algorithm: string
          child 1, max_sequences: int64
          child 2, max_tokens: int64
          child 3, window_size: int64
      child 3, compute_dtype: string
      child 4, device_type: string
      child 5, engine_sha256: string
      child 6, kernel_sha256: null
      child 7, numerical_policy: struct<autocast_dtype: string, autocast_enabled: bool, cuda_matmul_allow_tf32: bool, cudnn_allow_tf3 (... 339 chars omitted)
          child 0, autocast_dtype: string
          child 1, autocast_enabled: bool
          child 2, cuda_matmul_allow_tf32: bool
          child 3, cudnn_allow_tf32: bool
          child 4, deterministic_algorithms: bool
          child 5, esmc_fp8: bool
          child 6, esmc_precision: struct<converted_projections: int64, device: string, enabled: bool, reason: string, transformer_engi (... 17 chars omitted)
              child 0, converted_projections: int64
              child 1, device: string
              child 2, enabled: bool
              child
...
nt64
      child 3, version: string
  child 12, sae: null
  child 13, schema: string
  child 14, special_tokens: string
  child 15, structural: null
  child 16, tokenizer: struct<content_sha256: string, repository: string, revision: string>
      child 0, content_sha256: string
      child 1, repository: string
      child 2, revision: string
dtype: string
format: string
key: string
layout: string
positions: bool
width: int64
normalization: string
schema: string
max_residues: int64
special_tokens: string
hub_repo: string
base: string
random_init: null
store_kind: string
label: string
row_layout: string
streams: struct<final_mean_var: struct<descriptor_sha256: string, dtype: string, key: string, layout: string, (... 157 chars omitted)
  child 0, final_mean_var: struct<descriptor_sha256: string, dtype: string, key: string, layout: string, sparse_count: null, wi (... 11 chars omitted)
      child 0, descriptor_sha256: string
      child 1, dtype: string
      child 2, key: string
      child 3, layout: string
      child 4, sparse_count: null
      child 5, width: int64
  child 1, sae_max: struct<descriptor_sha256: string, dtype: string, key: string, layout: string, sparse_count: null, wi (... 11 chars omitted)
      child 0, descriptor_sha256: string
      child 1, dtype: string
      child 2, key: string
      child 3, layout: string
      child 4, sparse_count: null
      child 5, width: int64
volume: string
sae_layer: int64
volume_directory: string
model_state_sha256: string
to
{'base': Value('string'), 'hub_repo': Value('string'), 'label': Value('string'), 'max_residues': Value('int64'), 'model_state_sha256': Value('string'), 'normalization': Value('string'), 'random_init': Value('null'), 'row_layout': Value('string'), 'sae_layer': Value('int64'), 'schema': Value('string'), 'special_tokens': Value('string'), 'store_kind': Value('string'), 'streams': {'final_mean_var': {'descriptor_sha256': Value('string'), 'dtype': Value('string'), 'key': Value('string'), 'layout': Value('string'), 'sparse_count': Value('null'), 'width': Value('int64')}, 'sae_max': {'descriptor_sha256': Value('string'), 'dtype': Value('string'), 'key': Value('string'), 'layout': Value('string'), 'sparse_count': Value('null'), 'width': Value('int64')}}, 'volume': Value('string'), 'volume_directory': 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 2840, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, 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 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
              descriptor: struct<execution: struct<accumulator_dtype: string, attention_backend: string, batch_policy: struct< (... 1598 chars omitted)
                child 0, execution: struct<accumulator_dtype: string, attention_backend: string, batch_policy: struct<algorithm: string, (... 759 chars omitted)
                    child 0, accumulator_dtype: string
                    child 1, attention_backend: string
                    child 2, batch_policy: struct<algorithm: string, max_sequences: int64, max_tokens: int64, window_size: int64>
                        child 0, algorithm: string
                        child 1, max_sequences: int64
                        child 2, max_tokens: int64
                        child 3, window_size: int64
                    child 3, compute_dtype: string
                    child 4, device_type: string
                    child 5, engine_sha256: string
                    child 6, kernel_sha256: null
                    child 7, numerical_policy: struct<autocast_dtype: string, autocast_enabled: bool, cuda_matmul_allow_tf32: bool, cudnn_allow_tf3 (... 339 chars omitted)
                        child 0, autocast_dtype: string
                        child 1, autocast_enabled: bool
                        child 2, cuda_matmul_allow_tf32: bool
                        child 3, cudnn_allow_tf32: bool
                        child 4, deterministic_algorithms: bool
                        child 5, esmc_fp8: bool
                        child 6, esmc_precision: struct<converted_projections: int64, device: string, enabled: bool, reason: string, transformer_engi (... 17 chars omitted)
                            child 0, converted_projections: int64
                            child 1, device: string
                            child 2, enabled: bool
                            child
              ...
              nt64
                    child 3, version: string
                child 12, sae: null
                child 13, schema: string
                child 14, special_tokens: string
                child 15, structural: null
                child 16, tokenizer: struct<content_sha256: string, repository: string, revision: string>
                    child 0, content_sha256: string
                    child 1, repository: string
                    child 2, revision: string
              dtype: string
              format: string
              key: string
              layout: string
              positions: bool
              width: int64
              normalization: string
              schema: string
              max_residues: int64
              special_tokens: string
              hub_repo: string
              base: string
              random_init: null
              store_kind: string
              label: string
              row_layout: string
              streams: struct<final_mean_var: struct<descriptor_sha256: string, dtype: string, key: string, layout: string, (... 157 chars omitted)
                child 0, final_mean_var: struct<descriptor_sha256: string, dtype: string, key: string, layout: string, sparse_count: null, wi (... 11 chars omitted)
                    child 0, descriptor_sha256: string
                    child 1, dtype: string
                    child 2, key: string
                    child 3, layout: string
                    child 4, sparse_count: null
                    child 5, width: int64
                child 1, sae_max: struct<descriptor_sha256: string, dtype: string, key: string, layout: string, sparse_count: null, wi (... 11 chars omitted)
                    child 0, descriptor_sha256: string
                    child 1, dtype: string
                    child 2, key: string
                    child 3, layout: string
                    child 4, sparse_count: null
                    child 5, width: int64
              volume: string
              sae_layer: int64
              volume_directory: string
              model_state_sha256: string
              to
              {'base': Value('string'), 'hub_repo': Value('string'), 'label': Value('string'), 'max_residues': Value('int64'), 'model_state_sha256': Value('string'), 'normalization': Value('string'), 'random_init': Value('null'), 'row_layout': Value('string'), 'sae_layer': Value('int64'), 'schema': Value('string'), 'special_tokens': Value('string'), 'store_kind': Value('string'), 'streams': {'final_mean_var': {'descriptor_sha256': Value('string'), 'dtype': Value('string'), 'key': Value('string'), 'layout': Value('string'), 'sparse_count': Value('null'), 'width': Value('int64')}, 'sae_max': {'descriptor_sha256': Value('string'), 'dtype': Value('string'), 'key': Value('string'), 'layout': Value('string'), 'sparse_count': Value('null'), 'width': Value('int64')}}, 'volume': Value('string'), 'volume_directory': Value('string')}
              because column names don't match

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ESMC-6B pooled embeddings

One vector per protein from ESMC-6B, in the FastPLMs feature-store format, for every protein of Synthyra/canonical_embedding_sequences_v1. The per-token streams of interaction proteins are in Synthyra/esmc_6b_token_embeddings.

Each vector covers all l + 2 token rows of a protein (cropped from the N-terminus at 2046): row 0 is CLS, rows 1..l are the residues, row l + 1 is EOS, and padding is the only masked position. final_mean_var is the mean, then the population variance, of the final normalized hidden state. sae_max is the maximum of the SAE codes over those rows.

A row is keyed by the SHA-256 of the uppercased, whitespace-stripped sequence. The store only appends.

stream layout width dtype
final_mean_var dense 5120 float32
sae_max csr 16384 float32

Read it with foundry.embedding.open_canonical_view(root, inventory) (a FeatureView), or with fastplms.features.FeatureStore directly. canonical.json lists the streams and pins each descriptor. Model state SHA-256: 5379c6e4d602f3b0a4dc0fb6ca0d5609c0f743db61a212c06b938b8dee76b0ff.

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