Protein Embeddings
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14 items • Updated
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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
descriptor: struct<execution: struct<accumulator_dtype: string, attention_backend: string, batch_policy: struct< (... 1853 chars omitted)
child 0, execution: struct<accumulator_dtype: string, attention_backend: string, batch_policy: struct<algorithm: string, (... 640 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 (... 188 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, float32_matmul_precision: string
child 6, hardware: struct<cpu_capability: string, cuda_capability: list<item: int64>, cuda_name: string, machine: strin (... 2 chars omitted)
child 0, cpu_capability: string
child 1, cuda_capability: list<item: int64>
child 0, item
...
426 chars omitted)
child 0, decoder_hidden: 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, decoder_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 2, encoder_hidden: 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 3, encoder_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
unit: string
volume: string
label: string
row_layout: string
family: string
sae_layer: null
volume_directory: string
to
{'base': Value('string'), 'family': Value('string'), 'hub_repo': Value('string'), 'label': Value('string'), 'max_units': Value('int64'), 'model_state_sha256': Value('string'), 'normalization': Value('string'), 'pins': {'model': {'files': {'config.json': Value('string'), 'model.safetensors': Value('string'), 'special_tokens_map.json': Value('string'), 'tokenizer.json': Value('string'), 'tokenizer_config.json': Value('string')}, 'repository': Value('string'), 'revision': Value('string')}, 'tokenizer': {'files': {'special_tokens_map.json': Value('string'), 'tokenizer.json': Value('string'), 'tokenizer_config.json': Value('string')}, 'repository': Value('string'), 'revision': Value('string')}}, 'random_init': Value('null'), 'row_layout': Value('string'), 'sae_layer': Value('null'), 'schema': Value('string'), 'special_tokens': Value('string'), 'streams': {'decoder_hidden': {'descriptor_sha256': Value('string'), 'dtype': Value('string'), 'key': Value('string'), 'layout': Value('string'), 'sparse_count': Value('null'), 'width': Value('int64')}, 'decoder_mean_var': {'descriptor_sha256': Value('string'), 'dtype': Value('string'), 'key': Value('string'), 'layout': Value('string'), 'sparse_count': Value('null'), 'width': Value('int64')}, 'encoder_hidden': {'descriptor_sha256': Value('string'), 'dtype': Value('string'), 'key': Value('string'), 'layout': Value('string'), 'sparse_count': Value('null'), 'width': Value('int64')}, 'encoder_mean_var': {'descriptor_sha256': Value('string'), 'dtype': Value('string'), 'key': Value('string'), 'layout': Value('string'), 'sparse_count': Value('null'), 'width': Value('int64')}}, 'unit': Value('string'), '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 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
descriptor: struct<execution: struct<accumulator_dtype: string, attention_backend: string, batch_policy: struct< (... 1853 chars omitted)
child 0, execution: struct<accumulator_dtype: string, attention_backend: string, batch_policy: struct<algorithm: string, (... 640 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 (... 188 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, float32_matmul_precision: string
child 6, hardware: struct<cpu_capability: string, cuda_capability: list<item: int64>, cuda_name: string, machine: strin (... 2 chars omitted)
child 0, cpu_capability: string
child 1, cuda_capability: list<item: int64>
child 0, item
...
426 chars omitted)
child 0, decoder_hidden: 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, decoder_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 2, encoder_hidden: 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 3, encoder_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
unit: string
volume: string
label: string
row_layout: string
family: string
sae_layer: null
volume_directory: string
to
{'base': Value('string'), 'family': Value('string'), 'hub_repo': Value('string'), 'label': Value('string'), 'max_units': Value('int64'), 'model_state_sha256': Value('string'), 'normalization': Value('string'), 'pins': {'model': {'files': {'config.json': Value('string'), 'model.safetensors': Value('string'), 'special_tokens_map.json': Value('string'), 'tokenizer.json': Value('string'), 'tokenizer_config.json': Value('string')}, 'repository': Value('string'), 'revision': Value('string')}, 'tokenizer': {'files': {'special_tokens_map.json': Value('string'), 'tokenizer.json': Value('string'), 'tokenizer_config.json': Value('string')}, 'repository': Value('string'), 'revision': Value('string')}}, 'random_init': Value('null'), 'row_layout': Value('string'), 'sae_layer': Value('null'), 'schema': Value('string'), 'special_tokens': Value('string'), 'streams': {'decoder_hidden': {'descriptor_sha256': Value('string'), 'dtype': Value('string'), 'key': Value('string'), 'layout': Value('string'), 'sparse_count': Value('null'), 'width': Value('int64')}, 'decoder_mean_var': {'descriptor_sha256': Value('string'), 'dtype': Value('string'), 'key': Value('string'), 'layout': Value('string'), 'sparse_count': Value('null'), 'width': Value('int64')}, 'encoder_hidden': {'descriptor_sha256': Value('string'), 'dtype': Value('string'), 'key': Value('string'), 'layout': Value('string'), 'sparse_count': Value('null'), 'width': Value('int64')}, 'encoder_mean_var': {'descriptor_sha256': Value('string'), 'dtype': Value('string'), 'key': Value('string'), 'layout': Value('string'), 'sparse_count': Value('null'), 'width': Value('int64')}}, 'unit': Value('string'), 'volume': Value('string'), 'volume_directory': Value('string')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
SELFIES-TED-LARGE token embeddings
Per-token and pooled rows. Model: lhallee/SELFIES-TED-LARGE at revision 259f46e840edca8fbc6963b17972f0cd004469e3, weights SHA-256 db34a6917e7635aaa25d8ad7a799898dd476e38bc639e1f35a576981f165be5e.
A row is one molecule, keyed by the SHA-256 of its canonical SMILES (foundry.chemistry.canonicalize_smiles). The model reads its SELFIES, cut after a whole symbol at 1022 symbols. inventory/*.parquet lists each row's SMILES, SELFIES, symbol count and row count.
A molecule of l symbols is l + 2 token rows: row 0 CLS, rows 1..l the symbols, row l + 1 SEP. Padding is the only masked position, and a pooled vector (mean, then population variance) covers all l + 2 rows. decoder_* is the state Atlas-PLI reads (BartModel.last_hidden_state, the decoder teacher forced on the molecule); encoder_* is the encoder's last_hidden_state. This repository holds the pooled streams of its rows too; Synthyra/selfies_ted_large_pooled_embeddings holds them alone.
| stream | layout | width | dtype |
|---|---|---|---|
decoder_hidden |
ragged | 1024 | bfloat16 |
decoder_mean_var |
dense | 2048 | float32 |
encoder_hidden |
ragged | 1024 | bfloat16 |
encoder_mean_var |
dense | 2048 | 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. The store only appends.
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