Model type
DNA transformer encoder
Model
Nucleotide Transformer v2
Nucleotide Transformer v2 represents DNA using an encoder pretrained on multiple species.
Sources (7)
InstaDeepAI/nucleotide-transformer-v2-50m-multi-species: README.md; InstaDeepAI/nucleotide-transformer-v2-50m-multi-species: config.json; instadeepai/nucleotide-transformer: README.md; instadeepai/nucleotide-transformer: docs/nucleotide_transformer.md; instadeepai/nucleotide-transformer: docs/agro_nucleotide_transformer.md; instadeepai/nucleotide-transformer: docs/segment_nt.md; nt: Journal full-text XML · README.md: Model Summary, Training data and licence metadata; config.json; Nucleotide Transformer paper Methods: Architecture and Training (v2); source conflict with 50M card retained44 evaluations · 44 metric rows · 1 evaluated configuration using this model
How it worksNucleotide Transformer v2 workflow
Conceptual summary of the documented data flow; optional inputs and configured downstream stages must be reported for a reproducible evaluation.
Sources (7)
InstaDeepAI/nucleotide-transformer-v2-50m-multi-species: README.md; InstaDeepAI/nucleotide-transformer-v2-50m-multi-species: config.json; instadeepai/nucleotide-transformer: README.md; instadeepai/nucleotide-transformer: docs/nucleotide_transformer.md; instadeepai/nucleotide-transformer: docs/agro_nucleotide_transformer.md; instadeepai/nucleotide-transformer: docs/segment_nt.md; nt: Journal full-text XML · README.md: Model Summary, Training data and licence metadata; config.json; Nucleotide Transformer paper Methods: Architecture and Training (v2); source conflict with 50M card retainedOverview
Inputs
DNA sequences with tokenization determined by 6-mers and individual ambiguous/remainder bases.
Sources (7)
InstaDeepAI/nucleotide-transformer-v2-50m-multi-species: README.md; InstaDeepAI/nucleotide-transformer-v2-50m-multi-species: config.json; instadeepai/nucleotide-transformer: README.md; instadeepai/nucleotide-transformer: docs/nucleotide_transformer.md; instadeepai/nucleotide-transformer: docs/agro_nucleotide_transformer.md; instadeepai/nucleotide-transformer: docs/segment_nt.md; nt: Journal full-text XML · README.md: Model Summary, Training data and licence metadata; config.json; Nucleotide Transformer paper Methods: Architecture and Training (v2); source conflict with 50M card retainedOutputs
Contextual DNA embeddings and masked-token probabilities; downstream tasks need adaptation.
Sources (7)
InstaDeepAI/nucleotide-transformer-v2-50m-multi-species: README.md; InstaDeepAI/nucleotide-transformer-v2-50m-multi-species: config.json; instadeepai/nucleotide-transformer: README.md; instadeepai/nucleotide-transformer: docs/nucleotide_transformer.md; instadeepai/nucleotide-transformer: docs/agro_nucleotide_transformer.md; instadeepai/nucleotide-transformer: docs/segment_nt.md; nt: Journal full-text XML · README.md: Model Summary, Training data and licence metadata; config.json; Nucleotide Transformer paper Methods: Architecture and Training (v2); source conflict with 50M card retainedAccess
Official downloadable model/card and usage examples: https://huggingface.co/InstaDeepAI/nucleotide-transformer-v2-50m-multi-species
Sources (7)
InstaDeepAI/nucleotide-transformer-v2-50m-multi-species: README.md; InstaDeepAI/nucleotide-transformer-v2-50m-multi-species: config.json; instadeepai/nucleotide-transformer: README.md; instadeepai/nucleotide-transformer: docs/nucleotide_transformer.md; instadeepai/nucleotide-transformer: docs/agro_nucleotide_transformer.md; instadeepai/nucleotide-transformer: docs/segment_nt.md; nt: Journal full-text XML · README.md: Model Summary, Training data and licence metadata; config.json; Nucleotide Transformer paper Methods: Architecture and Training (v2); source conflict with 50M card retainedlimited source coverage · Automated source review, 2026-09-16. All specifications and missing details
Evaluations and results
44 evaluations · 44 metric rows. Different protocols are not a single leaderboard.
Filter evaluations
Applied filters: All linked evaluations
| Tested configuration | Protocol and dataset | Finding | Evidence and details |
|---|---|---|---|
| Configuration: NT-v2-50M-MS | Task: GENEB LINEAR-PROBE: Average macro-MCC across the 13 representative tasks, linear probe Dataset subset: GENEB representative task subset (GENEB split) | 0.511 macro_mcc correlation · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · source checkedMethods, coverage and sourceFrozen embeddings scored with a probe over the thirteen representative tasks, one from each functional category (Table 7). Aggregation: Not reported GENEB: Why Genomic Models Are Hard to Compare · Table 8, row(NT-v2-50M-MS), column(Linear MCC) |
| Configuration: NT-v2-50M-MS | Task: GENEB MLP-PROBE: Average macro-MCC across the 13 representative tasks, MLP probe Dataset subset: GENEB representative task subset (GENEB split) | 0.521 macro_mcc correlation · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · source checkedMethods, coverage and sourceNT-v2-50M-MS on GENEB MLP-PROBE: Average macro-MCC across the 13 representative tasks, MLP probe Frozen embeddings scored with a probe over the thirteen representative tasks, one from each functional category (Table 7). Aggregation: Not reported GENEB: Why Genomic Models Are Hard to Compare · Table 8, row(NT-v2-50M-MS), column(MLP MCC) |
| Configuration: N.T.-v2-50m | Task: NABench CCV-CORR-APTAMER: Fitness prediction on aptamer assays, supervised, contiguous cross validation Dataset subset: NABench aptamer assays (NABench split) | 0.056 spearman correlation · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · source checkedMethods, coverage and sourceScored supervised, contiguous cross validation across the NABench aptamer assays. Aggregation: Not reported NABench: Large-Scale Benchmarks of Nucleotide Foundation Models for Fitness Prediction · Table 11, row(N.T.-v2-50m), column(aptamer) |
| Configuration: N.T.-v2-50m | Task: NABench CCV-CORR-ENHANCER: Fitness prediction on enhancer assays, supervised, contiguous cross validation Dataset subset: NABench enhancer assays (NABench split) | 0.116 spearman correlation · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · source checkedMethods, coverage and sourceScored supervised, contiguous cross validation across the NABench enhancer assays. Aggregation: Not reported NABench: Large-Scale Benchmarks of Nucleotide Foundation Models for Fitness Prediction · Table 11, row(N.T.-v2-50m), column(enhancer) |
| Configuration: N.T.-v2-50m | Task: NABench CCV-CORR-MRNA: Fitness prediction on mRNA assays, supervised, contiguous cross validation Dataset subset: NABench mRNA assays (NABench split) | 0.073 spearman correlation · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · source checkedMethods, coverage and sourceScored supervised, contiguous cross validation across the NABench mRNA assays. Aggregation: Not reported NABench: Large-Scale Benchmarks of Nucleotide Foundation Models for Fitness Prediction · Table 11, row(N.T.-v2-50m), column(mRNA) |
| Configuration: N.T.-v2-50m | Task: NABench CCV-CORR-PROMOTER: Fitness prediction on promoter assays, supervised, contiguous cross validation Dataset subset: NABench promoter assays (NABench split) | 0.220 spearman correlation · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · source checkedMethods, coverage and sourceScored supervised, contiguous cross validation across the NABench promoter assays. Aggregation: Not reported NABench: Large-Scale Benchmarks of Nucleotide Foundation Models for Fitness Prediction · Table 11, row(N.T.-v2-50m), column(promoter) |
| Configuration: N.T.-v2-50m | Task: NABench CCV-CORR-RIBOZYME: Fitness prediction on ribozyme assays, supervised, contiguous cross validation Dataset subset: NABench ribozyme assays (NABench split) | 0.300 spearman correlation · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · source checkedMethods, coverage and sourceScored supervised, contiguous cross validation across the NABench ribozyme assays. Aggregation: Not reported NABench: Large-Scale Benchmarks of Nucleotide Foundation Models for Fitness Prediction · Table 11, row(N.T.-v2-50m), column(ribozyme) |
| Configuration: N.T.-v2-50m | Task: NABench DMS-CCV: Overall fitness prediction on NABench deep mutational scanning assays, Contiguous cross validation Spearman ρ Dataset subset: NABench deep mutational scanning assays (NABench split) | 0.220 spearman correlation · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · source checkedMethods, coverage and sourceAggregated by the NABench authors across NABench deep mutational scanning assays. Aggregation: Not reported NABench: Large-Scale Benchmarks of Nucleotide Foundation Models for Fitness Prediction · Table 6, row(N.T.-v2-50m), column(Contiguous cross validation Spearman ρ) |
| Configuration: N.T.-v2-50m | Task: NABench DMS-FS: Overall fitness prediction on NABench deep mutational scanning assays, Few-shot Spearman ρ Dataset subset: NABench deep mutational scanning assays (NABench split) | 0.110 spearman correlation · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · source checkedMethods, coverage and sourceAggregated by the NABench authors across NABench deep mutational scanning assays. Aggregation: Not reported NABench: Large-Scale Benchmarks of Nucleotide Foundation Models for Fitness Prediction · Table 6, row(N.T.-v2-50m), column(Few-shot Spearman ρ) |
| Configuration: N.T.-v2-50m | Task: NABench DMS-RCV: Overall fitness prediction on NABench deep mutational scanning assays, Random cross validation Spearman ρ Dataset subset: NABench deep mutational scanning assays (NABench split) | 0.465 spearman correlation · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · source checkedMethods, coverage and sourceAggregated by the NABench authors across NABench deep mutational scanning assays. Aggregation: Not reported NABench: Large-Scale Benchmarks of Nucleotide Foundation Models for Fitness Prediction · Table 6, row(N.T.-v2-50m), column(Random cross validation Spearman ρ) |
| Configuration: N.T.-v2-50m | Task: NABench DMS-ZS-AUC: Overall fitness prediction on NABench deep mutational scanning assays, Zero-shot AUC Dataset subset: NABench deep mutational scanning assays (NABench split) | 0.512 auc fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · source checkedMethods, coverage and sourceAggregated by the NABench authors across NABench deep mutational scanning assays. Aggregation: Not reported NABench: Large-Scale Benchmarks of Nucleotide Foundation Models for Fitness Prediction · Table 6, row(N.T.-v2-50m), column(Zero-shot AUC) |
| Configuration: N.T.-v2-50m | Task: NABench DMS-ZS-CORR: Overall fitness prediction on NABench deep mutational scanning assays, Zero-shot Spearman ρ Dataset subset: NABench deep mutational scanning assays (NABench split) | 0.097 spearman correlation · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · source checkedMethods, coverage and sourceAggregated by the NABench authors across NABench deep mutational scanning assays. Aggregation: Not reported NABench: Large-Scale Benchmarks of Nucleotide Foundation Models for Fitness Prediction · Table 6, row(N.T.-v2-50m), column(Zero-shot Spearman ρ) |
| Configuration: N.T.-v2-50m | Task: NABench DMS-ZS-MCC: Overall fitness prediction on NABench deep mutational scanning assays, Zero-shot MCC Dataset subset: NABench deep mutational scanning assays (NABench split) | 0.044 mcc correlation · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · source checkedMethods, coverage and sourceAggregated by the NABench authors across NABench deep mutational scanning assays. Aggregation: Not reported NABench: Large-Scale Benchmarks of Nucleotide Foundation Models for Fitness Prediction · Table 6, row(N.T.-v2-50m), column(Zero-shot MCC) |
| Configuration: N.T.-v2-50m | Task: NABench DMS-ZS-NDCG: Overall fitness prediction on NABench deep mutational scanning assays, Zero-shot NDCG Dataset subset: NABench deep mutational scanning assays (NABench split) | 0.349 ndcg fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · source checkedMethods, coverage and sourceAggregated by the NABench authors across NABench deep mutational scanning assays. Aggregation: Not reported NABench: Large-Scale Benchmarks of Nucleotide Foundation Models for Fitness Prediction · Table 6, row(N.T.-v2-50m), column(Zero-shot NDCG) |
| Configuration: N.T.-v2-50m | Task: NABench FS-CORR-APTAMER: Fitness prediction on aptamer assays, few-shot Dataset subset: NABench aptamer assays (NABench split) | 0.230 spearman correlation · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · source checkedMethods, coverage and sourceN.T.-v2-50m on NABench FS-CORR-APTAMER: Fitness prediction on aptamer assays, few-shot Scored few-shot across the NABench aptamer assays. Aggregation: Not reported NABench: Large-Scale Benchmarks of Nucleotide Foundation Models for Fitness Prediction · Table 9, row(N.T.-v2-50m), column(aptamer) |
| Configuration: N.T.-v2-50m | Task: NABench FS-CORR-ENHANCER: Fitness prediction on enhancer assays, few-shot Dataset subset: NABench enhancer assays (NABench split) | 0.026 spearman correlation · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · source checkedMethods, coverage and sourceN.T.-v2-50m on NABench FS-CORR-ENHANCER: Fitness prediction on enhancer assays, few-shot Scored few-shot across the NABench enhancer assays. Aggregation: Not reported NABench: Large-Scale Benchmarks of Nucleotide Foundation Models for Fitness Prediction · Table 9, row(N.T.-v2-50m), column(enhancer) |
| Configuration: N.T.-v2-50m | Task: NABench FS-CORR-MRNA: Fitness prediction on mRNA assays, few-shot Dataset subset: NABench mRNA assays (NABench split) | 0.214 spearman correlation · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · source checkedMethods, coverage and sourceN.T.-v2-50m on NABench FS-CORR-MRNA: Fitness prediction on mRNA assays, few-shot Scored few-shot across the NABench mRNA assays. Aggregation: Not reported NABench: Large-Scale Benchmarks of Nucleotide Foundation Models for Fitness Prediction · Table 9, row(N.T.-v2-50m), column(mRNA) |
| Configuration: N.T.-v2-50m | Task: NABench FS-CORR-PROMOTER: Fitness prediction on promoter assays, few-shot Dataset subset: NABench promoter assays (NABench split) | 0.061 spearman correlation · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · source checkedMethods, coverage and sourceN.T.-v2-50m on NABench FS-CORR-PROMOTER: Fitness prediction on promoter assays, few-shot Scored few-shot across the NABench promoter assays. Aggregation: Not reported NABench: Large-Scale Benchmarks of Nucleotide Foundation Models for Fitness Prediction · Table 9, row(N.T.-v2-50m), column(promoter) |
| Configuration: N.T.-v2-50m | Task: NABench FS-CORR-RIBOZYME: Fitness prediction on ribozyme assays, few-shot Dataset subset: NABench ribozyme assays (NABench split) | 0.090 spearman correlation · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · source checkedMethods, coverage and sourceN.T.-v2-50m on NABench FS-CORR-RIBOZYME: Fitness prediction on ribozyme assays, few-shot Scored few-shot across the NABench ribozyme assays. Aggregation: Not reported NABench: Large-Scale Benchmarks of Nucleotide Foundation Models for Fitness Prediction · Table 9, row(N.T.-v2-50m), column(ribozyme) |
| Configuration: N.T.-v2-50m | Task: NABench FS-CORR-TRNA: Fitness prediction on tRNA assays, few-shot Dataset subset: NABench tRNA assays (NABench split) | 0.327 spearman correlation · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · source checkedMethods, coverage and sourceN.T.-v2-50m on NABench FS-CORR-TRNA: Fitness prediction on tRNA assays, few-shot Scored few-shot across the NABench tRNA assays. Aggregation: Not reported NABench: Large-Scale Benchmarks of Nucleotide Foundation Models for Fitness Prediction · Table 9, row(N.T.-v2-50m), column(tRNA) |
| Configuration: N.T.-v2-50m | Task: NABench RCV-CORR-APTAMER: Fitness prediction on aptamer assays, supervised, random cross validation Dataset subset: NABench aptamer assays (NABench split) | 0.462 spearman correlation · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · source checkedMethods, coverage and sourceScored supervised, random cross validation across the NABench aptamer assays. Aggregation: Not reported NABench: Large-Scale Benchmarks of Nucleotide Foundation Models for Fitness Prediction · Table 10, row(N.T.-v2-50m), column(aptamer) |
| Configuration: N.T.-v2-50m | Task: NABench RCV-CORR-ENHANCER: Fitness prediction on enhancer assays, supervised, random cross validation Dataset subset: NABench enhancer assays (NABench split) | 0.148 spearman correlation · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · source checkedMethods, coverage and sourceScored supervised, random cross validation across the NABench enhancer assays. Aggregation: Not reported NABench: Large-Scale Benchmarks of Nucleotide Foundation Models for Fitness Prediction · Table 10, row(N.T.-v2-50m), column(enhancer) |
| Configuration: N.T.-v2-50m | Task: NABench RCV-CORR-MRNA: Fitness prediction on mRNA assays, supervised, random cross validation Dataset subset: NABench mRNA assays (NABench split) | 0.570 spearman correlation · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · source checkedMethods, coverage and sourceScored supervised, random cross validation across the NABench mRNA assays. Aggregation: Not reported NABench: Large-Scale Benchmarks of Nucleotide Foundation Models for Fitness Prediction · Table 10, row(N.T.-v2-50m), column(mRNA) |
| Configuration: N.T.-v2-50m | Task: NABench RCV-CORR-PROMOTER: Fitness prediction on promoter assays, supervised, random cross validation Dataset subset: NABench promoter assays (NABench split) | 0.632 spearman correlation · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · source checkedMethods, coverage and sourceScored supervised, random cross validation across the NABench promoter assays. Aggregation: Not reported NABench: Large-Scale Benchmarks of Nucleotide Foundation Models for Fitness Prediction · Table 10, row(N.T.-v2-50m), column(promoter) |
| Configuration: N.T.-v2-50m | Task: NABench RCV-CORR-RIBOZYME: Fitness prediction on ribozyme assays, supervised, random cross validation Dataset subset: NABench ribozyme assays (NABench split) | 0.464 spearman correlation · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · source checkedMethods, coverage and sourceScored supervised, random cross validation across the NABench ribozyme assays. Aggregation: Not reported NABench: Large-Scale Benchmarks of Nucleotide Foundation Models for Fitness Prediction · Table 10, row(N.T.-v2-50m), column(ribozyme) |
Source checking is not independent reproduction. Release 2026-09-23-2b89723c6dd9.
Related configurations, pipelines and services
These configurations, services and pipelines use this model within their own configurations. Their results, where available, are not assigned to the underlying model.
- nt-v2–50m-multi-species Pipeline · 8 metric rows
Use this model
How it works, versions and access
Related profile: Nucleotide Transformer. This page retains the exact record and its evaluation context.
Versions and evaluated configurations
- NT-v2-50M-MS · family
- N.T.-v2-50m · family
How it works
How it works
Nucleotide Transformer v2 represents DNA using an encoder pretrained on multiple species. Encoder-only transformer with 6-mer tokenization, rotary position embeddings and SwiGLU feed-forward layers. The documented inputs are DNA sequences with tokenization determined by 6-mers and individual ambiguous/remainder bases. The output consists of contextual DNA embeddings and masked-token probabilities; downstream tasks need adaptation.
Sources (7)
InstaDeepAI/nucleotide-transformer-v2-50m-multi-species: README.md; InstaDeepAI/nucleotide-transformer-v2-50m-multi-species: config.json; instadeepai/nucleotide-transformer: README.md; instadeepai/nucleotide-transformer: docs/nucleotide_transformer.md; instadeepai/nucleotide-transformer: docs/agro_nucleotide_transformer.md; instadeepai/nucleotide-transformer: docs/segment_nt.md; nt: Journal full-text XML · README.md: Model Summary, Training data and licence metadata; config.json; Nucleotide Transformer paper Methods: Architecture and Training (v2); source conflict with 50M card retainedVersions and reproducibility
nucleotide-transformer-v2-50m-multi-species is the linked checkpoint; distinguish it from other family scales. Source conflict retained: the model card describes 1,000-token pretraining, while the official NT-v2 documentation describes 2,048-token capacity. Token and base counts must be stated separately.
Sources (7)
InstaDeepAI/nucleotide-transformer-v2-50m-multi-species: README.md; InstaDeepAI/nucleotide-transformer-v2-50m-multi-species: config.json; instadeepai/nucleotide-transformer: README.md; instadeepai/nucleotide-transformer: docs/nucleotide_transformer.md; instadeepai/nucleotide-transformer: docs/agro_nucleotide_transformer.md; instadeepai/nucleotide-transformer: docs/segment_nt.md; nt: Journal full-text XML · README.md: Model Summary, Training data and licence metadata; config.json; Nucleotide Transformer paper Methods: Architecture and Training (v2); source conflict with 50M card retainedStrengths, limitations and unresolved questions
Strengths and limitations
Strengths and considerations
- The v2 architecture extends the token context relative to v1 while providing several parameter scales.
Sources (7)
InstaDeepAI/nucleotide-transformer-v2-50m-multi-species: README.md; InstaDeepAI/nucleotide-transformer-v2-50m-multi-species: config.json; instadeepai/nucleotide-transformer: README.md; instadeepai/nucleotide-transformer: docs/nucleotide_transformer.md; instadeepai/nucleotide-transformer: docs/agro_nucleotide_transformer.md; instadeepai/nucleotide-transformer: docs/segment_nt.md; nt: Journal full-text XML · README.md: Model Summary, Training data and licence metadata; config.json; Nucleotide Transformer paper Methods: Architecture and Training (v2); source conflict with 50M card retained
Limitations and conditions
- Token length is not identical to base-pair length: ambiguous bases consume individual tokens. The linked 50M card does not make every v2 checkpoint identical.
Sources (7)
InstaDeepAI/nucleotide-transformer-v2-50m-multi-species: README.md; InstaDeepAI/nucleotide-transformer-v2-50m-multi-species: config.json; instadeepai/nucleotide-transformer: README.md; instadeepai/nucleotide-transformer: docs/nucleotide_transformer.md; instadeepai/nucleotide-transformer: docs/agro_nucleotide_transformer.md; instadeepai/nucleotide-transformer: docs/segment_nt.md; nt: Journal full-text XML · README.md: Model Summary, Training data and licence metadata; config.json; Nucleotide Transformer paper Methods: Architecture and Training (v2); source conflict with 50M card retained
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: catalog-model-nt-v2Specifications
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.
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.
142 evidence rows matching the loaded filters
| 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 | instadeepai/nucleotide-transformer: README.md README.md: Model Summary, Training data and licence metadata; config.json; Nucleotide Transformer paper Methods: Architecture and Training (v2); source conflict with 50M card retained Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 2dc37b86e16a6970fbc731751f7719d9f676f7f9 | source checked automated source review · 2026-09-16 Audit detailsInspected 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: Source artifact SHA-256: Hash scope: SHA-256 of retrieved original artifact bytes Format: original_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 | instadeepai/nucleotide-transformer: docs/segment_nt.md README.md: Model Summary, Training data and licence metadata; config.json; Nucleotide Transformer paper Methods: Architecture and Training (v2); source conflict with 50M card retained Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 2dc37b86e16a6970fbc731751f7719d9f676f7f9 | source checked automated source review · 2026-09-16 Audit detailsInspected 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: Source artifact SHA-256: Hash scope: SHA-256 of retrieved original artifact bytes Format: original_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 | InstaDeepAI/nucleotide-transformer-v2-50m-multi-species: README.md README.md: Model Summary, Training data and licence metadata; config.json; Nucleotide Transformer paper Methods: Architecture and Training (v2); source conflict with 50M card retained Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 81b29e5786726d891dbf929404ef20adca5b36f1 | source checked automated source review · 2026-09-16 Audit detailsInspected 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: Source artifact SHA-256: Hash scope: SHA-256 of retrieved original artifact bytes Format: original_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 | instadeepai/nucleotide-transformer: docs/agro_nucleotide_transformer.md README.md: Model Summary, Training data and licence metadata; config.json; Nucleotide Transformer paper Methods: Architecture and Training (v2); source conflict with 50M card retained Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 2dc37b86e16a6970fbc731751f7719d9f676f7f9 | source checked automated source review · 2026-09-16 Audit detailsInspected 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: Source artifact SHA-256: Hash scope: SHA-256 of retrieved original artifact bytes Format: original_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 | instadeepai/nucleotide-transformer: docs/nucleotide_transformer.md README.md: Model Summary, Training data and licence metadata; config.json; Nucleotide Transformer paper Methods: Architecture and Training (v2); source conflict with 50M card retained Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 2dc37b86e16a6970fbc731751f7719d9f676f7f9 | source checked automated source review · 2026-09-16 Audit detailsInspected 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: Source artifact SHA-256: Hash scope: SHA-256 of retrieved original artifact bytes Format: original_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 | InstaDeepAI/nucleotide-transformer-v2-50m-multi-species: config.json README.md: Model Summary, Training data and licence metadata; config.json; Nucleotide Transformer paper Methods: Architecture and Training (v2); source conflict with 50M card retained Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 81b29e5786726d891dbf929404ef20adca5b36f1 | source checked automated source review · 2026-09-16 Audit detailsInspected 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: Source artifact SHA-256: Hash scope: SHA-256 of retrieved original artifact bytes Format: original_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 | nt: Journal full-text XML README.md: Model Summary, Training data and licence metadata; config.json; Nucleotide Transformer paper Methods: Architecture and Training (v2); source conflict with 50M card retained Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Retrieved page snapshot; no immutable publisher revision supplied | source checked automated source review · 2026-09-16 Audit detailsInspected 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: Source artifact SHA-256: Hash scope: SHA-256 of retrieved original artifact bytes Format: original_artifact |
Diagram steps
| instadeepai/nucleotide-transformer: README.md README.md: Model Summary, Training data and licence metadata; config.json; Nucleotide Transformer paper Methods: Architecture and Training (v2); source conflict with 50M card retained Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 2dc37b86e16a6970fbc731751f7719d9f676f7f9 | source checked automated source review · 2026-09-16 Audit detailsInspected 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: Source artifact SHA-256: Hash scope: SHA-256 of retrieved original artifact bytes Format: original_artifact |
Diagram steps
| instadeepai/nucleotide-transformer: docs/segment_nt.md README.md: Model Summary, Training data and licence metadata; config.json; Nucleotide Transformer paper Methods: Architecture and Training (v2); source conflict with 50M card retained Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 2dc37b86e16a6970fbc731751f7719d9f676f7f9 | source checked automated source review · 2026-09-16 Audit detailsInspected 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: Source artifact SHA-256: Hash scope: SHA-256 of retrieved original artifact bytes Format: original_artifact |
Diagram steps
| InstaDeepAI/nucleotide-transformer-v2-50m-multi-species: README.md README.md: Model Summary, Training data and licence metadata; config.json; Nucleotide Transformer paper Methods: Architecture and Training (v2); source conflict with 50M card retained Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 81b29e5786726d891dbf929404ef20adca5b36f1 | source checked automated source review · 2026-09-16 Audit detailsInspected 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: Source artifact SHA-256: Hash scope: SHA-256 of retrieved original artifact bytes Format: original_artifact |
Sources and history
View linked audit checks and correction history
Release 2026-09-23-2b89723c6dd9 · Record review: discovered
9 source records and release history
- Nucleotide Transformer v2 official resource · Original source · Not reported
- InstaDeepAI/nucleotide-transformer-v2-50m-multi-species: README.md · Original source · 81b29e5786726d891dbf929404ef20adca5b36f1
- InstaDeepAI/nucleotide-transformer-v2-50m-multi-species: config.json · Original source · 81b29e5786726d891dbf929404ef20adca5b36f1
- instadeepai/nucleotide-transformer: README.md · Original source · 2dc37b86e16a6970fbc731751f7719d9f676f7f9
- instadeepai/nucleotide-transformer: docs/nucleotide_transformer.md · Original source · 2dc37b86e16a6970fbc731751f7719d9f676f7f9
- instadeepai/nucleotide-transformer: docs/agro_nucleotide_transformer.md · Original source · 2dc37b86e16a6970fbc731751f7719d9f676f7f9
- instadeepai/nucleotide-transformer: docs/segment_nt.md · Original source · 2dc37b86e16a6970fbc731751f7719d9f676f7f9
- nt: Journal full-text XML · Original source · Retrieved page snapshot; no immutable publisher revision supplied
- instadeepai/nucleotide-transformer: LICENSE.md · Original source · 2dc37b86e16a6970fbc731751f7719d9f676f7f9
Technical metadata and extraction receipts
Stable ID: catalog-model-nt-v2
- areas
- dna-genomes
- method types
- foundation model
- entity level
- family
- version
- 50M multi-species
- reported name
- Nucleotide Transformer v2
- access
- Public checkpoint.
- method type
- foundation model
- historical missing metadata
- checkpoint revision: not_yet_extracted; training data: not_yet_extracted; licence: not_yet_extracted
- 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-4abb9affb1a9e5438c91; evidence-official-6b79ddfdd330693bf4fb; evidence-official-18d8f4d5fc3f6616922d; evidence-official-657e83427ab59f3aec83; evidence-official-56f02d45976d011d80aa; evidence-official-4920952f9b3c4b8909a0; evidence-official-aadbeb0f10ec55d34f5f; source locator: README.md: Model Summary, Training data and licence metadata; config.json; Nucleotide Transformer paper Methods: Architecture and Training (v2); source conflict with 50M card retained; ambiguities: None recorded
Related records
- variant of: Nucleotide Transformer
- family: NT-v2-50M-MS
- subject: Nucleotide Transformer v2: variant of Nucleotide Transformer
- uses model: nt-v2–50m-multi-species
- family: N.T.-v2-50m