Model type
Geometric encoder and inverse-folding transformer
Model
ESM-IF1
ESM-IF1 designs protein sequences conditioned on backbone coordinates.
Sources
facebookresearch/esm: README.md · README.md: Inverse folding and Pre-trained ModelsHow it worksESM-IF1 workflow
Conceptual summary of the documented data flow; optional inputs and configured downstream stages must be reported for a reproducible evaluation.
Sources
facebookresearch/esm: README.md · README.md: Inverse folding and Pre-trained ModelsOverview
Inputs
Protein backbone atom coordinates; the model supports missing backbone spans.
Outputs
Sampled protein sequences or conditional sequence likelihoods.
Access
Official project documentation and implementation: https://github.com/facebookresearch/esm
Sources
facebookresearch/esm: README.md · README.md: Inverse folding and Pre-trained Modelslimited source coverage · Automated source review, 2026-09-16. All specifications and missing details
Evaluations and results
11 evaluations · 15 results. Different protocols are not a single leaderboard.
Filter evaluations
Applied filters: All linked evaluations
| Tested configuration | Protocol and dataset | Finding | Evidence and details |
|---|---|---|---|
| Configuration: ESM-IF1 | Task: ProteinBench IF-DE-NOVO-BACKBONES-BASED-SEQUENCE-DESIGN-LENGTH-100-PLDDT: De novo backbones based sequence design, length 100 pLDDT Dataset subset: CASP, CAMEO and de novo backbones (ProteinBench split) | 88.8 plddt score · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceInverse folding: recover a sequence for a given backbone. Values are the median over repeated runs. Aggregation: Not reported proteinbench primary benchmark evidence · Table 2, row(ESM-IF1), column(De novo backbones based sequence design, length 100 pLDDT ↑) |
| Configuration: ESM-IF1 | Task: ProteinBench IF-DE-NOVO-BACKBONES-BASED-SEQUENCE-DESIGN-LENGTH-100-SCTM: De novo backbones based sequence design, length 100 scTM Dataset subset: CASP, CAMEO and de novo backbones (ProteinBench split) | 0.81 sctm score · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceInverse folding: recover a sequence for a given backbone. Values are the median over repeated runs. Aggregation: Not reported proteinbench primary benchmark evidence · Table 2, row(ESM-IF1), column(De novo backbones based sequence design, length 100 scTM ↑) |
| Configuration: ESM-IF1 | Task: ProteinBench IF-DE-NOVO-BACKBONES-BASED-SEQUENCE-DESIGN-LENGTH-200-PLDDT: De novo backbones based sequence design, length 200 pLDDT Dataset subset: CASP, CAMEO and de novo backbones (ProteinBench split) | 69.7 plddt score · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceInverse folding: recover a sequence for a given backbone. Values are the median over repeated runs. Aggregation: Not reported proteinbench primary benchmark evidence · Table 2, row(ESM-IF1), column(De novo backbones based sequence design, length 200 pLDDT ↑) |
| Configuration: ESM-IF1 | Task: ProteinBench IF-DE-NOVO-BACKBONES-BASED-SEQUENCE-DESIGN-LENGTH-200-SCTM: De novo backbones based sequence design, length 200 scTM Dataset subset: CASP, CAMEO and de novo backbones (ProteinBench split) | 0.635 sctm score · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceInverse folding: recover a sequence for a given backbone. Values are the median over repeated runs. Aggregation: Not reported proteinbench primary benchmark evidence · Table 2, row(ESM-IF1), column(De novo backbones based sequence design, length 200 scTM ↑) |
| Configuration: ESM-IF1 | Task: ProteinBench IF-DE-NOVO-BACKBONES-BASED-SEQUENCE-DESIGN-LENGTH-300-PLDDT: De novo backbones based sequence design, length 300 pLDDT Dataset subset: CASP, CAMEO and de novo backbones (ProteinBench split) | 74.4 plddt score · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceInverse folding: recover a sequence for a given backbone. Values are the median over repeated runs. Aggregation: Not reported proteinbench primary benchmark evidence · Table 2, row(ESM-IF1), column(De novo backbones based sequence design, length 300 pLDDT ↑) |
| Configuration: ESM-IF1 | Task: ProteinBench IF-DE-NOVO-BACKBONES-BASED-SEQUENCE-DESIGN-LENGTH-300-SCTM: De novo backbones based sequence design, length 300 scTM Dataset subset: CASP, CAMEO and de novo backbones (ProteinBench split) | 0.336 sctm score · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceInverse folding: recover a sequence for a given backbone. Values are the median over repeated runs. Aggregation: Not reported proteinbench primary benchmark evidence · Table 2, row(ESM-IF1), column(De novo backbones based sequence design, length 300 scTM ↑) |
| Configuration: ESM-IF1 | Task: ProteinBench IF-DE-NOVO-BACKBONES-BASED-SEQUENCE-DESIGN-LENGTH-400-PLDDT: De novo backbones based sequence design, length 400 pLDDT Dataset subset: CASP, CAMEO and de novo backbones (ProteinBench split) | 64.6 plddt score · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceInverse folding: recover a sequence for a given backbone. Values are the median over repeated runs. Aggregation: Not reported proteinbench primary benchmark evidence · Table 2, row(ESM-IF1), column(De novo backbones based sequence design, length 400 pLDDT ↑) |
| Configuration: ESM-IF1 | Task: ProteinBench IF-DE-NOVO-BACKBONES-BASED-SEQUENCE-DESIGN-LENGTH-400-SCTM: De novo backbones based sequence design, length 400 scTM Dataset subset: CASP, CAMEO and de novo backbones (ProteinBench split) | 0.449 sctm score · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceInverse folding: recover a sequence for a given backbone. Values are the median over repeated runs. Aggregation: Not reported proteinbench primary benchmark evidence · Table 2, row(ESM-IF1), column(De novo backbones based sequence design, length 400 scTM ↑) |
| Configuration: ESM-IF1 | Task: ProteinBench IF-DE-NOVO-BACKBONES-BASED-SEQUENCE-DESIGN-LENGTH-500-PLDDT: De novo backbones based sequence design, length 500 pLDDT Dataset subset: CASP, CAMEO and de novo backbones (ProteinBench split) | 59 plddt score · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceInverse folding: recover a sequence for a given backbone. Values are the median over repeated runs. Aggregation: Not reported proteinbench primary benchmark evidence · Table 2, row(ESM-IF1), column(De novo backbones based sequence design, length 500 pLDDT ↑) |
| Configuration: ESM-IF1 | Task: ProteinBench IF-DE-NOVO-BACKBONES-BASED-SEQUENCE-DESIGN-LENGTH-500-SCTM: De novo backbones based sequence design, length 500 scTM Dataset subset: CASP, CAMEO and de novo backbones (ProteinBench split) | 0.462 sctm score · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceInverse folding: recover a sequence for a given backbone. Values are the median over repeated runs. Aggregation: Not reported proteinbench primary benchmark evidence · Table 2, row(ESM-IF1), column(De novo backbones based sequence design, length 500 scTM ↑) |
| Configuration: ESM-IF1 | Task: ProteinGym ZS-SUB-AUC: Zero-shot substitutions, AUC Dataset subset: ProteinGym substitution DMS assays (ProteinGym split) | 0.73 auc fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceESM-IF1 on ProteinGym ZS-SUB-AUC: Zero-shot substitutions, AUC Zero-shot scoring of substitution assays, averaged over assays with the correction the paper describes. Aggregation: Not reported ProteinGym: Large-Scale Benchmarks for Protein Fitness Prediction and Design · Table 2, row(Inverse ESM-IF1), column(Zero-shot substitutions, AUC) |
| Configuration: ESM-IF1 | Task: ProteinGym ZS-SUB-MCC: Zero-shot substitutions, MCC Dataset subset: ProteinGym substitution DMS assays (ProteinGym split) | 0.331 mcc correlation · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceESM-IF1 on ProteinGym ZS-SUB-MCC: Zero-shot substitutions, MCC Zero-shot scoring of substitution assays, averaged over assays with the correction the paper describes. Aggregation: Not reported ProteinGym: Large-Scale Benchmarks for Protein Fitness Prediction and Design · Table 2, row(Inverse ESM-IF1), column(Zero-shot substitutions, MCC) |
| Configuration: ESM-IF1 | Task: ProteinGym ZS-SUB-NDCG: Zero-shot substitutions, NDCG@10% Dataset subset: ProteinGym substitution DMS assays (ProteinGym split) | 0.748 ndcg fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceESM-IF1 on ProteinGym ZS-SUB-NDCG: Zero-shot substitutions, NDCG@10% Zero-shot scoring of substitution assays, averaged over assays with the correction the paper describes. Aggregation: Not reported ProteinGym: Large-Scale Benchmarks for Protein Fitness Prediction and Design · Table 2, row(Inverse ESM-IF1), column(Zero-shot substitutions, NDCG@10%) |
| Configuration: ESM-IF1 | Task: ProteinGym ZS-SUB-RECALL: Zero-shot substitutions, top 10% recall Dataset subset: ProteinGym substitution DMS assays (ProteinGym split) | 0.223 recall fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceESM-IF1 on ProteinGym ZS-SUB-RECALL: Zero-shot substitutions, top 10% recall Zero-shot scoring of substitution assays, averaged over assays with the correction the paper describes. Aggregation: Not reported ProteinGym: Large-Scale Benchmarks for Protein Fitness Prediction and Design · Table 2, row(Inverse ESM-IF1), column(Zero-shot substitutions, top 10% recall) |
| Configuration: ESM-IF1 | Task: ProteinGym ZS-SUB-SPEARMAN: Zero-shot substitutions, Spearman Dataset subset: ProteinGym substitution DMS assays (ProteinGym split) | 0.422 spearman correlation · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceESM-IF1 on ProteinGym ZS-SUB-SPEARMAN: Zero-shot substitutions, Spearman Zero-shot scoring of substitution assays, averaged over assays with the correction the paper describes. Aggregation: Not reported ProteinGym: Large-Scale Benchmarks for Protein Fitness Prediction and Design · Table 2, row(Inverse ESM-IF1), column(Zero-shot substitutions, Spearman) |
Source checking is not independent reproduction. Release 2026-09-29-06401fd5b220.
Use this model
How it works, versions and access
Versions and evaluated configurations
How it works
How it works
ESM-IF1 designs protein sequences conditioned on backbone coordinates. Geometric-vector-perceptron input processing followed by a sequence-to-sequence transformer. The documented inputs are protein backbone atom coordinates; the model supports missing backbone spans. The output consists of sampled protein sequences or conditional sequence likelihoods.
Sources
facebookresearch/esm: README.md · README.md: Inverse folding and Pre-trained ModelsVersions and reproducibility
esm_if1_gvp4_t16_142M_UR50. The applicable input limits require configuration-specific checking.
Sources
facebookresearch/esm: README.md · README.md: Inverse folding and Pre-trained ModelsStrengths, limitations and unresolved questions
Strengths and limitations
Strengths and considerations
- Structure-conditioned design can use partially missing backbones because training included span masking.
Sources
facebookresearch/esm: README.md · README.md: Inverse folding and Pre-trained Models
Limitations and conditions
- The public checkpoint name contains 142M but the README parameter table reports 124M. This discrepancy is retained rather than silently selecting a total.
Sources
facebookresearch/esm: README.md · README.md: Inverse folding and Pre-trained Models
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-esm-if1Specifications
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.
| Property | Description and evidence |
|---|---|
| Model type | Geometric encoder and inverse-folding transformerSourcesfacebookresearch/esm: README.md · README.md: Inverse folding and Pre-trained Models |
| Architecture | Geometric-vector-perceptron input processing followed by a sequence-to-sequence transformer.Sourcesfacebookresearch/esm: README.md · README.md: Inverse folding and Pre-trained Models |
| Inputs | Protein backbone atom coordinates; the model supports missing backbone spans.Sourcesfacebookresearch/esm: README.md · README.md: Inverse folding and Pre-trained Models |
| Outputs | Sampled protein sequences or conditional sequence likelihoods.Sourcesfacebookresearch/esm: README.md · README.md: Inverse folding and Pre-trained Models |
| Parameters | The official checkpoint identifier contains 142M but the same repository model table states 124M. Both values are retained as a source discrepancy, without choosing a total.Sourcesfacebookresearch/esm: README.md · README.md: Inverse folding and Pre-trained Models |
| Known versions | esm_if1_gvp4_t16_142M_UR50.Sourcesfacebookresearch/esm: README.md · README.md: Inverse folding and Pre-trained Models |
| Training data | CATH 4.3 and predicted UniRef50 structures; README reports 12M structures predicted by AlphaFold2.Sourcesfacebookresearch/esm: README.md · README.md: Inverse folding and Pre-trained Models |
| Training cutoff | The official model table identifies CATH 4.3 and predicted UniRef50 structures, but does not state a common latest-structure or sequence date. · Not reported in inspected sourcesSourcesfacebookresearch/esm: README.md · README.md: Inverse folding and Pre-trained Models |
| Context limits | The reviewed inverse-folding usage and model table do not establish a universal maximum backbone length; the structural graph and selected inference configuration determine resource use. · Not reported in inspected sourcesSourcesfacebookresearch/esm: README.md · README.md: Inverse folding and Pre-trained Models |
| 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 sourcesSources (2)facebookresearch/esm: README.md; facebookresearch/esm: LICENSE · README.md: Inverse folding and Pre-trained Models; LICENSE: licence text |
| Access | Official project documentation and implementation: https://github.com/facebookresearch/esmSourcesfacebookresearch/esm: README.md · README.md: Inverse folding and Pre-trained Models |
| Code licence | MITSourcesfacebookresearch/esm: LICENSE · LICENSE: licence text |
Applicable tests and references
Applicability is distinct from a completed evaluation.
- ProteinBench · Proposed association
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.
21 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 | facebookresearch/esm: README.md README.md: Inverse folding and Pre-trained Models Version: 2b369911bb5b4b0dda914521b9475cad1656b2ac | 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
| facebookresearch/esm: README.md README.md: Inverse folding and Pre-trained Models Version: 2b369911bb5b4b0dda914521b9475cad1656b2ac | 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 title ESM-IF1 workflow Individual claims | facebookresearch/esm: README.md README.md: Inverse folding and Pre-trained Models Version: 2b369911bb5b4b0dda914521b9475cad1656b2ac | 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 |
| Model type Geometric encoder and inverse-folding transformer Individual claims | facebookresearch/esm: README.md README.md: Inverse folding and Pre-trained Models Version: 2b369911bb5b4b0dda914521b9475cad1656b2ac | 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 |
| Architecture Geometric-vector-perceptron input processing followed by a sequence-to-sequence transformer. Individual claims | facebookresearch/esm: README.md README.md: Inverse folding and Pre-trained Models Version: 2b369911bb5b4b0dda914521b9475cad1656b2ac | 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 |
| Access Official project documentation and implementation: https://github.com/facebookresearch/esm Individual claims | facebookresearch/esm: README.md README.md: Inverse folding and Pre-trained Models Version: 2b369911bb5b4b0dda914521b9475cad1656b2ac | 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 |
| Code licence MIT Individual claims | facebookresearch/esm: LICENSE LICENSE: licence text Version: 2b369911bb5b4b0dda914521b9475cad1656b2ac | 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 |
| Inputs Protein backbone atom coordinates; the model supports missing backbone spans. Individual claims | facebookresearch/esm: README.md README.md: Inverse folding and Pre-trained Models Version: 2b369911bb5b4b0dda914521b9475cad1656b2ac | 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 |
| Outputs Sampled protein sequences or conditional sequence likelihoods. Individual claims | facebookresearch/esm: README.md README.md: Inverse folding and Pre-trained Models Version: 2b369911bb5b4b0dda914521b9475cad1656b2ac | 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 |
| Parameters The official checkpoint identifier contains 142M but the same repository model table states 124M. Both values are retained as a source discrepancy, without choosing a total. Individual claims | facebookresearch/esm: README.md README.md: Inverse folding and Pre-trained Models Version: 2b369911bb5b4b0dda914521b9475cad1656b2ac | 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 2026-09-29-06401fd5b220 · Record review: discovered
3 source records and release history
- facebookresearch/esm official source · Original source · 2b369911bb5b4b0dda914521b9475cad1656b2ac
- facebookresearch/esm: README.md · Original source · 2b369911bb5b4b0dda914521b9475cad1656b2ac
- facebookresearch/esm: LICENSE · Original source · 2b369911bb5b4b0dda914521b9475cad1656b2ac
Technical metadata and extraction receipts
Stable ID: discovery-model-esm-if1
- areas
- protein-structure
- access
- official_source_linked
- benchmark applicability
- candidate; not evidence of a reported evaluation
- candidate benchmark ids
- discovery-benchmark-proteinbench
- entity level
- family
- reported name
- ESM-IF1
- version
- Not reported
- historical missing metadata
- checkpoint: unextracted; code licence: unextracted; parameters: unextracted; training cutoff: unextracted; training data: unextracted; version: unextracted; weights licence: unextracted
- 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-29d4b229a3aa426a6dfb; source locator: README.md: Inverse folding and Pre-trained Models; ambiguities: None recorded
Related records
- applicable to: ProteinBench
- family: ESM-IF1
- family: ESM-IF1