Model

TAPE Transformer

The TAPE Transformer learns contextual protein representations using masked-residue pretraining and a task-specific prediction head.

Sources (7)

songlab-cal/tape: README.md; songlab-cal/tape: tape/models/modeling_lstm.py; songlab-cal/tape: tape/models/modeling_resnet.py; songlab-cal/tape: tape/models/modeling_unirep.py; songlab-cal/tape: tape/models/modeling_onehot.py; songlab-cal/tape: tape/models/modeling_bert.py; tape: Primary paper PDF · tape/models/modeling_bert.py: configuration and model classes; README.md: opening maintenance warning, Examples and Data; June 2019 TAPE preprint Sections 4.1,5 and AppendixA.3

7 evaluations · 7 results

How it worksTAPE Transformer workflow

Conceptual summary of the documented data flow; optional inputs and configured downstream stages must be reported for a reproducible evaluation.

Sources (7)

Overview

Model type

BERT-style protein transformer encoder

Inputs

Amino-acid sequence in the tokenizer expected by the selected implementation.

Outputs

Residue/sequence representations and predictions from the chosen task head.

Access

Official project documentation and implementation: https://github.com/songlab-cal/tape

Sources (7)

limited source coverage · Automated source review, 2026-09-16. All specifications and missing details

Evaluations and results

7 evaluations · 7 results. Different protocols are not a single leaderboard.

Filter evaluations

Tested model or methodProtocolDatasetEvaluation setupMetricEvidence origin

Applied filters: All linked evaluations

Exact evaluated configurations and original reported results
Tested configuration	Protocol and dataset	Finding	Evidence and details
Configuration: TAPE Transformer (ATOM3D baseline) (cited as [Rao et al., 2019])	Task: ATOM3D MSP: Mutation stability prediction Dataset subset: ATOM3D MSP (ATOM3D split)	0.554 auroc fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source TAPE Transformer (ATOM3D baseline) on ATOM3D MSP: Mutation stability prediction Trained and scored under the ATOM3D split for this task. Asterisks in the paper mark a run whose training data differed. Aggregation: Not reported ATOM3D: Tasks On Molecules in Three Dimensions · Table 4, row(MSP AUROC), column([Rao et al., 2019])
Configuration: TAPE Transformer (ATOM3D baseline) (cited as [Rao et al., 2019])	Task: ATOM3D RES: Residue identity Dataset subset: ATOM3D RES (ATOM3D split)	0.3 accuracy fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source TAPE Transformer (ATOM3D baseline) on ATOM3D RES: Residue identity Trained and scored under the ATOM3D split for this task. Asterisks in the paper mark a run whose training data differed. Aggregation: Not reported ATOM3D: Tasks On Molecules in Three Dimensions · Table 4, row(RES accuracy), column([Rao et al., 2019])
Model: TAPE Transformer	Task: TAPE Fluorescence Dataset: TAPE Fluorescence source dataset	0.68 Spearman's rho correlation · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source TAPE Fluorescence Transformer leaderboard evaluation Train/validation at most 3 mutations; test 4–15 mutations from the GFP parent Aggregation: Not reported songlab-cal/tape official source; tape primary benchmark evidence · README.md > Leaderboard > Fluorescence; row Transformer; column Spearman's rho
Model: TAPE Transformer	Task: TAPE Stability Dataset: TAPE Stability source dataset	0.73 Spearman's rho correlation · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source TAPE Stability Transformer leaderboard evaluation Test 17 one-mutation neighbourhoods around candidate proteins; train on broad experimental design rounds Aggregation: Not reported songlab-cal/tape official source; tape primary benchmark evidence · README.md > Leaderboard > Stability; row Transformer; column Spearman's rho
Model: TAPE Transformer	Task: TAPE Contact Prediction Dataset: ProteinNet CASP12	0.36 precision at L/5 fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source TAPE Transformer: ProteinNet CASP12 CASP12 test, 30% sequence-identity partition; medium/long-range contacts Aggregation: Not reported tape primary benchmark evidence · Table2,p.7,row4(Self-supervised pretraining/Transformer),columnContact prediction
Model: TAPE Transformer	Task: TAPE Secondary Structure Dataset: CB513	0.73 accuracy fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source TAPE Transformer: CB513 CB513 test set; train/test proteins filtered at 25% sequence identity Aggregation: Not reported tape primary benchmark evidence · Table2,p.7,row4(Self-supervised pretraining/Transformer),columnSecondary structure
Model: TAPE Transformer	Task: TAPE Remote Homology Detection Dataset: SCOP1.75 fold-level test	0.21 accuracy fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source TAPE Transformer: SCOP1.75 fold-level test Held-out evolutionary groups; fold-level classification into 1,195 folds Aggregation: Not reported tape primary benchmark evidence · Table2,p.7,row4(Self-supervised pretraining/Transformer),columnRemote homology

Source checking is not independent reproduction. Release 2026-09-29-06401fd5b220.

Use this model

How it works, versions and access

Versions and evaluated configurations

TAPE Transformer (ATOM3D baseline) · family

How it works

The TAPE Transformer learns contextual protein representations using masked-residue pretraining and a task-specific prediction head. The June 2019 preprint uses 12 transformer layers, width 512 and eight heads (38M parameters). The later PyTorch BertConfig defaults to width 768 and 12 heads; these are different configurations. The documented inputs are amino-acid sequence in the tokenizer expected by the selected implementation. The output consists of residue/sequence representations and predictions from the chosen task head.

Sources (7)

Versions and reproducibility

June 2019 TAPE preprint configurations and the later PyTorch package are distinct; the current README warns it is not an exact reproduction. The inspected default BertConfig sets max_position_embeddings to 8,096; this is an implementation default, not evidence that a historical TAPE checkpoint was trained at that length.

Sources (7)

Strengths, limitations and unresolved questions

Strengths and limitations

Strengths and considerations

Provides a defined reference architecture that can be paired with the same downstream tasks as other protein representations.
Sources (7)
songlab-cal/tape: README.md; songlab-cal/tape: tape/models/modeling_lstm.py; songlab-cal/tape: tape/models/modeling_resnet.py; songlab-cal/tape: tape/models/modeling_unirep.py; songlab-cal/tape: tape/models/modeling_onehot.py; songlab-cal/tape: tape/models/modeling_bert.py; tape: Primary paper PDF · tape/models/modeling_bert.py: configuration and model classes; README.md: opening maintenance warning, Examples and Data; June 2019 TAPE preprint Sections 4.1,5 and AppendixA.3

Limitations and conditions

The maintainers explicitly state that the current PyTorch repository is not an exact reproduction of the original TensorFlow paper code; training maintenance was discontinued. The default implementation reserves 8,096 position embeddings; this is an implementation setting, not proof of training or evaluation at that length.
Sources (7)
songlab-cal/tape: README.md; songlab-cal/tape: tape/models/modeling_lstm.py; songlab-cal/tape: tape/models/modeling_resnet.py; songlab-cal/tape: tape/models/modeling_unirep.py; songlab-cal/tape: tape/models/modeling_onehot.py; songlab-cal/tape: tape/models/modeling_bert.py; tape: Primary paper PDF · tape/models/modeling_bert.py: configuration and model classes; README.md: opening maintenance warning, Examples and Data; June 2019 TAPE preprint Sections 4.1,5 and AppendixA.3

Profile review details

Inspected pinned official documentation, relevant implementation files and named primary-paper sections. Claims are limited to those artifacts. Remaining field extraction and identity conflicts are explicit; no new performance claims, model runs or human review are implied.

Stable record: discovery-model-tape-transformer

Specifications

Inputs, training, access and other details

Explanatory profile: limited source coverage · Automated source review, 2026-09-16. Review applies to the cited claims; unresolved fields are listed below. Numerical results retain their own review status.

Inputs, outputs and configuration
Property	Description and evidence
Model type	BERT-style protein transformer encoder Sources (7) songlab-cal/tape: README.md; songlab-cal/tape: tape/models/modeling_lstm.py; songlab-cal/tape: tape/models/modeling_resnet.py; songlab-cal/tape: tape/models/modeling_unirep.py; songlab-cal/tape: tape/models/modeling_onehot.py; songlab-cal/tape: tape/models/modeling_bert.py; tape: Primary paper PDF · tape/models/modeling_bert.py: configuration and model classes; README.md: opening maintenance warning, Examples and Data; June 2019 TAPE preprint Sections 4.1,5 and AppendixA.3
Architecture	The June 2019 preprint uses 12 transformer layers, width 512 and eight heads (38M parameters). The later PyTorch BertConfig defaults to width 768 and 12 heads; these are different configurations. Sources (7) songlab-cal/tape: README.md; songlab-cal/tape: tape/models/modeling_lstm.py; songlab-cal/tape: tape/models/modeling_resnet.py; songlab-cal/tape: tape/models/modeling_unirep.py; songlab-cal/tape: tape/models/modeling_onehot.py; songlab-cal/tape: tape/models/modeling_bert.py; tape: Primary paper PDF · tape/models/modeling_bert.py: configuration and model classes; README.md: opening maintenance warning, Examples and Data; June 2019 TAPE preprint Sections 4.1,5 and AppendixA.3
Inputs	Amino-acid sequence in the tokenizer expected by the selected implementation. Sources (7) songlab-cal/tape: README.md; songlab-cal/tape: tape/models/modeling_lstm.py; songlab-cal/tape: tape/models/modeling_resnet.py; songlab-cal/tape: tape/models/modeling_unirep.py; songlab-cal/tape: tape/models/modeling_onehot.py; songlab-cal/tape: tape/models/modeling_bert.py; tape: Primary paper PDF · tape/models/modeling_bert.py: configuration and model classes; README.md: opening maintenance warning, Examples and Data; June 2019 TAPE preprint Sections 4.1,5 and AppendixA.3
Outputs	Residue/sequence representations and predictions from the chosen task head. Sources (7) songlab-cal/tape: README.md; songlab-cal/tape: tape/models/modeling_lstm.py; songlab-cal/tape: tape/models/modeling_resnet.py; songlab-cal/tape: tape/models/modeling_unirep.py; songlab-cal/tape: tape/models/modeling_onehot.py; songlab-cal/tape: tape/models/modeling_bert.py; tape: Primary paper PDF · tape/models/modeling_bert.py: configuration and model classes; README.md: opening maintenance warning, Examples and Data; June 2019 TAPE preprint Sections 4.1,5 and AppendixA.3
Parameters	38M for the June 2019 preprint Transformer; do not apply that total to the later PyTorch defaults or every task head. Sources (7) songlab-cal/tape: README.md; songlab-cal/tape: tape/models/modeling_lstm.py; songlab-cal/tape: tape/models/modeling_resnet.py; songlab-cal/tape: tape/models/modeling_unirep.py; songlab-cal/tape: tape/models/modeling_onehot.py; songlab-cal/tape: tape/models/modeling_bert.py; tape: Primary paper PDF · tape/models/modeling_bert.py: configuration and model classes; README.md: opening maintenance warning, Examples and Data; June 2019 TAPE preprint Sections 4.1,5 and AppendixA.3
Known versions	June 2019 TAPE preprint configurations and the later PyTorch package are distinct; the current README warns it is not an exact reproduction. Sources (7) songlab-cal/tape: README.md; songlab-cal/tape: tape/models/modeling_lstm.py; songlab-cal/tape: tape/models/modeling_resnet.py; songlab-cal/tape: tape/models/modeling_unirep.py; songlab-cal/tape: tape/models/modeling_onehot.py; songlab-cal/tape: tape/models/modeling_bert.py; tape: Primary paper PDF · tape/models/modeling_bert.py: configuration and model classes; README.md: opening maintenance warning, Examples and Data; June 2019 TAPE preprint Sections 4.1,5 and AppendixA.3
Training data	The June 2019 TAPE preprint uses 31M Pfam domains, with held-out families and a separate random split; downstream task heads are fitted on their own task data. Sources (7) songlab-cal/tape: README.md; songlab-cal/tape: tape/models/modeling_lstm.py; songlab-cal/tape: tape/models/modeling_resnet.py; songlab-cal/tape: tape/models/modeling_unirep.py; songlab-cal/tape: tape/models/modeling_onehot.py; songlab-cal/tape: tape/models/modeling_bert.py; tape: Primary paper PDF · tape/models/modeling_bert.py: configuration and model classes; README.md: opening maintenance warning, Examples and Data; June 2019 TAPE preprint Sections 4.1,5 and AppendixA.3
Training cutoff	The June 2019 TAPE preprint identifies the Pfam-domain corpus and split procedure but does not state one latest-sequence deposition date. Later package defaults are a different implementation. · Not reported in inspected sources Sources (7) songlab-cal/tape: README.md; songlab-cal/tape: tape/models/modeling_lstm.py; songlab-cal/tape: tape/models/modeling_resnet.py; songlab-cal/tape: tape/models/modeling_unirep.py; songlab-cal/tape: tape/models/modeling_onehot.py; songlab-cal/tape: tape/models/modeling_bert.py; tape: Primary paper PDF · tape/models/modeling_bert.py: configuration and model classes; README.md: opening maintenance warning, Examples and Data; June 2019 TAPE preprint Sections 4.1,5 and AppendixA.3
Context limits	The inspected default BertConfig sets max_position_embeddings to 8,096; this is an implementation default, not evidence that a historical TAPE checkpoint was trained at that length. Sources (7) songlab-cal/tape: README.md; songlab-cal/tape: tape/models/modeling_lstm.py; songlab-cal/tape: tape/models/modeling_resnet.py; songlab-cal/tape: tape/models/modeling_unirep.py; songlab-cal/tape: tape/models/modeling_onehot.py; songlab-cal/tape: tape/models/modeling_bert.py; tape: Primary paper PDF · tape/models/modeling_bert.py: configuration and model classes; README.md: opening maintenance warning, Examples and Data; June 2019 TAPE preprint Sections 4.1,5 and AppendixA.3
Weights licence	Separate checkpoint-distribution terms are not stated in the inspected release documentation and licence material. The source-code licence alone is not recorded as an explicit weight grant. · Not reported in inspected sources Sources (8) songlab-cal/tape: README.md; songlab-cal/tape: tape/models/modeling_lstm.py; songlab-cal/tape: tape/models/modeling_resnet.py; songlab-cal/tape: tape/models/modeling_unirep.py; songlab-cal/tape: tape/models/modeling_onehot.py; songlab-cal/tape: tape/models/modeling_bert.py; tape: Primary paper PDF; songlab-cal/tape: LICENSE · tape/models/modeling_bert.py: configuration and model classes; README.md: opening maintenance warning, Examples and Data; June 2019 TAPE preprint Sections 4.1,5 and AppendixA.3; LICENSE: licence text
Access	Official project documentation and implementation: https://github.com/songlab-cal/tape Sources (7) songlab-cal/tape: README.md; songlab-cal/tape: tape/models/modeling_lstm.py; songlab-cal/tape: tape/models/modeling_resnet.py; songlab-cal/tape: tape/models/modeling_unirep.py; songlab-cal/tape: tape/models/modeling_onehot.py; songlab-cal/tape: tape/models/modeling_bert.py; tape: Primary paper PDF · tape/models/modeling_bert.py: configuration and model classes; README.md: opening maintenance warning, Examples and Data; June 2019 TAPE preprint Sections 4.1,5 and AppendixA.3
Code licence	BSD-3-Clause Sources songlab-cal/tape: LICENSE · LICENSE: licence text

Evidence

Source checking verifies the cited claim or transcription. It does not establish independent reproduction.

Evidence table

Inspect claims, sources and review details

Trace each statement to its source and review. A context-only reference supports the record generally; it does not verify an individual field. Source checking does not reproduce an experiment.

One row per statement and cited source. Multiple citations are not independent evaluations. Shared locators are labelled explicitly.

135 evidence rows matching the loaded filters

Claims, original sources and review scope · Release 2026-09-29-06401fd5b220
Property and statement	Original source and location	Review and provenance
Diagram caption Conceptual summary of the documented data flow; optional inputs and configured downstream stages must be reported for a reproducible evaluation. Individual claims	songlab-cal/tape: README.md Original source ↗ tape/models/modeling_bert.py: configuration and model classes; README.md: opening maintenance warning, Examples and Data; June 2019 TAPE preprint Sections 4.1,5 and AppendixA.3 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 6d345c2b2bbf52cd32cf179325c222afd92aec7e Retrieved: 2026-09-16T19:46:20.570146+00:00	source checked automated source review · 2026-09-16 Audit details Inspected pinned official documentation, relevant implementation files and named primary-paper sections. Claims are limited to those artifacts. Remaining field extraction and identity conflicts are explicit; no new performance claims, model runs or human review are implied. Field: `attributes.profile.diagram.caption` Source artifact SHA-256: `b28c74fe3cd6b69a8ba6d84891d0539e54dfef882abd5ed4d11ed0b029bb477a` Hash scope: SHA-256 of retrieved original artifact bytes Format: original_artifact Inspected artifact
Diagram caption Conceptual summary of the documented data flow; optional inputs and configured downstream stages must be reported for a reproducible evaluation. Individual claims	songlab-cal/tape: tape/models/modeling_unirep.py Original source ↗ tape/models/modeling_bert.py: configuration and model classes; README.md: opening maintenance warning, Examples and Data; June 2019 TAPE preprint Sections 4.1,5 and AppendixA.3 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 6d345c2b2bbf52cd32cf179325c222afd92aec7e Retrieved: 2026-09-16T19:46:20.570146+00:00	source checked automated source review · 2026-09-16 Audit details Inspected pinned official documentation, relevant implementation files and named primary-paper sections. Claims are limited to those artifacts. Remaining field extraction and identity conflicts are explicit; no new performance claims, model runs or human review are implied. Field: `attributes.profile.diagram.caption` Source artifact SHA-256: `f6a0da726a8bcdd40640fab39c0814a56d6188531b44a3ce6e7e7137755c9a02` Hash scope: SHA-256 of retrieved original artifact bytes Format: original_artifact Inspected artifact
Diagram caption Conceptual summary of the documented data flow; optional inputs and configured downstream stages must be reported for a reproducible evaluation. Individual claims	songlab-cal/tape: tape/models/modeling_onehot.py Original source ↗ tape/models/modeling_bert.py: configuration and model classes; README.md: opening maintenance warning, Examples and Data; June 2019 TAPE preprint Sections 4.1,5 and AppendixA.3 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 6d345c2b2bbf52cd32cf179325c222afd92aec7e Retrieved: 2026-09-16T19:46:20.570146+00:00	source checked automated source review · 2026-09-16 Audit details Inspected pinned official documentation, relevant implementation files and named primary-paper sections. Claims are limited to those artifacts. Remaining field extraction and identity conflicts are explicit; no new performance claims, model runs or human review are implied. Field: `attributes.profile.diagram.caption` Source artifact SHA-256: `546fab3931d2ae7b6a0ee06ff64c6bcedf2d58b460e5aa90be623b0895befe43` Hash scope: SHA-256 of retrieved original artifact bytes Format: original_artifact Inspected artifact
Diagram caption Conceptual summary of the documented data flow; optional inputs and configured downstream stages must be reported for a reproducible evaluation. Individual claims	songlab-cal/tape: tape/models/modeling_lstm.py Original source ↗ tape/models/modeling_bert.py: configuration and model classes; README.md: opening maintenance warning, Examples and Data; June 2019 TAPE preprint Sections 4.1,5 and AppendixA.3 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 6d345c2b2bbf52cd32cf179325c222afd92aec7e Retrieved: 2026-09-16T19:46:20.570146+00:00	source checked automated source review · 2026-09-16 Audit details Inspected pinned official documentation, relevant implementation files and named primary-paper sections. Claims are limited to those artifacts. Remaining field extraction and identity conflicts are explicit; no new performance claims, model runs or human review are implied. Field: `attributes.profile.diagram.caption` Source artifact SHA-256: `e857bc4d6d551915a375116208f7f74b286e7fc88d0d54f54b2746b2fb02e1ca` Hash scope: SHA-256 of retrieved original artifact bytes Format: original_artifact Inspected artifact
Diagram caption Conceptual summary of the documented data flow; optional inputs and configured downstream stages must be reported for a reproducible evaluation. Individual claims	tape: Primary paper PDF Original source ↗ tape/models/modeling_bert.py: configuration and model classes; README.md: opening maintenance warning, Examples and Data; June 2019 TAPE preprint Sections 4.1,5 and AppendixA.3 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 1906.08230v1 Retrieved: 2026-09-16T20:23:48.238777+00:00	source checked automated source review · 2026-09-16 Audit details Inspected pinned official documentation, relevant implementation files and named primary-paper sections. Claims are limited to those artifacts. Remaining field extraction and identity conflicts are explicit; no new performance claims, model runs or human review are implied. Field: `attributes.profile.diagram.caption` Source artifact SHA-256: `6ee0c3e6e870635cba8fa67e0a4abc5598c0ab2a10ba127a46b67ac450ae0168` Hash scope: SHA-256 of retrieved original artifact bytes Format: original_artifact Inspected artifact
Diagram caption Conceptual summary of the documented data flow; optional inputs and configured downstream stages must be reported for a reproducible evaluation. Individual claims	songlab-cal/tape: tape/models/modeling_resnet.py Original source ↗ tape/models/modeling_bert.py: configuration and model classes; README.md: opening maintenance warning, Examples and Data; June 2019 TAPE preprint Sections 4.1,5 and AppendixA.3 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 6d345c2b2bbf52cd32cf179325c222afd92aec7e Retrieved: 2026-09-16T19:46:20.570146+00:00	source checked automated source review · 2026-09-16 Audit details Inspected pinned official documentation, relevant implementation files and named primary-paper sections. Claims are limited to those artifacts. Remaining field extraction and identity conflicts are explicit; no new performance claims, model runs or human review are implied. Field: `attributes.profile.diagram.caption` Source artifact SHA-256: `fc97f083f059f5b587d568aa0c32f7cca227e247160a7e22e3a168aef1469ebe` Hash scope: SHA-256 of retrieved original artifact bytes Format: original_artifact Inspected artifact
Diagram caption Conceptual summary of the documented data flow; optional inputs and configured downstream stages must be reported for a reproducible evaluation. Individual claims	songlab-cal/tape: tape/models/modeling_bert.py Original source ↗ tape/models/modeling_bert.py: configuration and model classes; README.md: opening maintenance warning, Examples and Data; June 2019 TAPE preprint Sections 4.1,5 and AppendixA.3 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 6d345c2b2bbf52cd32cf179325c222afd92aec7e Retrieved: 2026-09-16T19:46:20.570146+00:00	source checked automated source review · 2026-09-16 Audit details Inspected pinned official documentation, relevant implementation files and named primary-paper sections. Claims are limited to those artifacts. Remaining field extraction and identity conflicts are explicit; no new performance claims, model runs or human review are implied. Field: `attributes.profile.diagram.caption` Source artifact SHA-256: `eba47206598a0e93e2f662d9c87343222556f236ac37373236e3970c43fb521d` Hash scope: SHA-256 of retrieved original artifact bytes Format: original_artifact Inspected artifact
Diagram steps Protein sequence Residue and position embeddings Transformer encoder Task head Individual claims	songlab-cal/tape: README.md Original source ↗ tape/models/modeling_bert.py: configuration and model classes; README.md: opening maintenance warning, Examples and Data; June 2019 TAPE preprint Sections 4.1,5 and AppendixA.3 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 6d345c2b2bbf52cd32cf179325c222afd92aec7e Retrieved: 2026-09-16T19:46:20.570146+00:00	source checked automated source review · 2026-09-16 Audit details Inspected pinned official documentation, relevant implementation files and named primary-paper sections. Claims are limited to those artifacts. Remaining field extraction and identity conflicts are explicit; no new performance claims, model runs or human review are implied. Field: `attributes.profile.diagram.steps` Source artifact SHA-256: `b28c74fe3cd6b69a8ba6d84891d0539e54dfef882abd5ed4d11ed0b029bb477a` Hash scope: SHA-256 of retrieved original artifact bytes Format: original_artifact Inspected artifact
Diagram steps Protein sequence Residue and position embeddings Transformer encoder Task head Individual claims	songlab-cal/tape: tape/models/modeling_unirep.py Original source ↗ tape/models/modeling_bert.py: configuration and model classes; README.md: opening maintenance warning, Examples and Data; June 2019 TAPE preprint Sections 4.1,5 and AppendixA.3 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 6d345c2b2bbf52cd32cf179325c222afd92aec7e Retrieved: 2026-09-16T19:46:20.570146+00:00	source checked automated source review · 2026-09-16 Audit details Inspected pinned official documentation, relevant implementation files and named primary-paper sections. Claims are limited to those artifacts. Remaining field extraction and identity conflicts are explicit; no new performance claims, model runs or human review are implied. Field: `attributes.profile.diagram.steps` Source artifact SHA-256: `f6a0da726a8bcdd40640fab39c0814a56d6188531b44a3ce6e7e7137755c9a02` Hash scope: SHA-256 of retrieved original artifact bytes Format: original_artifact Inspected artifact
Diagram steps Protein sequence Residue and position embeddings Transformer encoder Task head Individual claims	songlab-cal/tape: tape/models/modeling_onehot.py Original source ↗ tape/models/modeling_bert.py: configuration and model classes; README.md: opening maintenance warning, Examples and Data; June 2019 TAPE preprint Sections 4.1,5 and AppendixA.3 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 6d345c2b2bbf52cd32cf179325c222afd92aec7e Retrieved: 2026-09-16T19:46:20.570146+00:00	source checked automated source review · 2026-09-16 Audit details Inspected pinned official documentation, relevant implementation files and named primary-paper sections. Claims are limited to those artifacts. Remaining field extraction and identity conflicts are explicit; no new performance claims, model runs or human review are implied. Field: `attributes.profile.diagram.steps` Source artifact SHA-256: `546fab3931d2ae7b6a0ee06ff64c6bcedf2d58b460e5aa90be623b0895befe43` Hash scope: SHA-256 of retrieved original artifact bytes Format: original_artifact Inspected artifact

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Release 2026-09-29-06401fd5b220 · Record review: discovered

9 source records and release history

songlab-cal/tape official source · Original source · 6d345c2b2bbf52cd32cf179325c222afd92aec7e
songlab-cal/tape: README.md · Original source · 6d345c2b2bbf52cd32cf179325c222afd92aec7e
songlab-cal/tape: tape/models/modeling_lstm.py · Original source · 6d345c2b2bbf52cd32cf179325c222afd92aec7e
songlab-cal/tape: tape/models/modeling_resnet.py · Original source · 6d345c2b2bbf52cd32cf179325c222afd92aec7e
songlab-cal/tape: tape/models/modeling_unirep.py · Original source · 6d345c2b2bbf52cd32cf179325c222afd92aec7e
songlab-cal/tape: tape/models/modeling_onehot.py · Original source · 6d345c2b2bbf52cd32cf179325c222afd92aec7e
songlab-cal/tape: tape/models/modeling_bert.py · Original source · 6d345c2b2bbf52cd32cf179325c222afd92aec7e
tape: Primary paper PDF · Original source · 1906.08230v1
songlab-cal/tape: LICENSE · Original source · 6d345c2b2bbf52cd32cf179325c222afd92aec7e

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Stable ID: discovery-model-tape-transformer

areas: protein-function
entity level: method
reported name: Transformer
version: Not reported
historical missing metadata: checkpoint: unreported; version: unreported
metadata review scope: historical_missing_metadata preserves the original discovery state. Current descriptive evidence and missingness are recorded in profile.facts; numerical-result review is separate.
entity classification: review date: 2026-09-17; rationale: The cited profile describes a named learned biological predictor or representation model/family. Preserve this identity separately from task-specific fitting, individual checkpoints, pipelines and hosted access.; source ids: evidence-official-028db5eeb224def23456; evidence-official-1aae5efd1b27ae9c761a; evidence-official-3cec54ed6ded9cb0a092; evidence-official-044ad0df4e4fe48a2125; evidence-official-12d43bf3076a93fc4ee7; evidence-official-c303652f3d79132a00c2; evidence-official-362b9cef071111dfe343; source locator: tape/models/modeling_bert.py: configuration and model classes; README.md: opening maintenance warning, Examples and Data; June 2019 TAPE preprint Sections 4.1,5 and AppendixA.3; ambiguities: This record covers the named representation model architecture/recipe. Source-version architectural differences and exact evaluated configurations remain explicit; no common checkpoint is inferred.

Related records

family: TAPE Transformer (ATOM3D baseline)
model: TAPE Fluorescence Transformer leaderboard evaluation
model: TAPE Stability Transformer leaderboard evaluation
model: TAPE Transformer: SCOP1.75 fold-level test
model: TAPE Transformer: CB513
model: TAPE Transformer: ProteinNet CASP12

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