Nucleotide Transformer pre-training and probing compute
Training compute of Nucleotide Transformer
All models were trained on Cambridge-1 (16 nodes of eight A100 GPUs, 128 GPUs). The 500M-parameter models trained on one node for a day; the 2.5B-parameter models used the whole cluster for 28 days; NT-v2 models (50M to 500M) trained on one node for a day. Probing embeddings took 2 days on one 8-A100 node, and fitting 760,000 downstream models took 2.5 days on 3,000 CPUs.
Descriptive fact transcribed from the pinned source.
Evidence
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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.
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6 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| Claimed field training_compute Context-only references | Nucleotide Transformer: building and evaluating robust foundation models for human genomics (Nature Methods) Methods, 'Data preparation > Hardware', paragraphs 1 and 2: 'The 500M-parameter models were trained on a single node for a day, whereas the 2.5B-parameter models required the whole cluster for 28 days to be trained.' Version: Nature Methods 22, 287-297 (published online 2024-11-28); PMC11810778 full-text XML | not individually reviewed No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Source location Methods, 'Data preparation > Hardware', paragraphs 1 and 2: 'The 500M-parameter models were trained on a single node for a day, whereas the 2.5B-parameter models required the whole cluster for 28 days to be trained.' Context-only references | Nucleotide Transformer: building and evaluating robust foundation models for human genomics (Nature Methods) Methods, 'Data preparation > Hardware', paragraphs 1 and 2: 'The 500M-parameter models were trained on a single node for a day, whereas the 2.5B-parameter models required the whole cluster for 28 days to be trained.' Version: Nature Methods 22, 287-297 (published online 2024-11-28); PMC11810778 full-text XML | not individually reviewed No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Claimed value All models were trained on Cambridge-1 (16 nodes of eight A100 GPUs, 128 GPUs). The 500M-parameter models trained on one node for a day; the 2.5B-parameter models used the whole cluster for 28 days; NT-v2 models (50M to 500M) trained on one node for a day. Probing embeddings took 2 days on one 8-A100 node, and fitting 760,000 downstream models took 2.5 days on 3,000 CPUs. Context-only references | Nucleotide Transformer: building and evaluating robust foundation models for human genomics (Nature Methods) Methods, 'Data preparation > Hardware', paragraphs 1 and 2: 'The 500M-parameter models were trained on a single node for a day, whereas the 2.5B-parameter models required the whole cluster for 28 days to be trained.' Version: Nature Methods 22, 287-297 (published online 2024-11-28); PMC11810778 full-text XML | not individually reviewed No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Description Descriptive fact transcribed from the pinned source. Context-only references | Nucleotide Transformer: building and evaluating robust foundation models for human genomics (Nature Methods) Methods, 'Data preparation > Hardware', paragraphs 1 and 2: 'The 500M-parameter models were trained on a single node for a day, whereas the 2.5B-parameter models required the whole cluster for 28 days to be trained.' Version: Nature Methods 22, 287-297 (published online 2024-11-28); PMC11810778 full-text XML | not individually reviewed No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Relationship: subject discovery-model-nucleotide-transformer Context-only references | Nucleotide Transformer: building and evaluating robust foundation models for human genomics (Nature Methods) Methods, 'Data preparation > Hardware', paragraphs 1 and 2: 'The 500M-parameter models were trained on a single node for a day, whereas the 2.5B-parameter models required the whole cluster for 28 days to be trained.' Version: Nature Methods 22, 287-297 (published online 2024-11-28); PMC11810778 full-text XML | not individually reviewed No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Name Nucleotide Transformer pre-training and probing compute Context-only references | Nucleotide Transformer: building and evaluating robust foundation models for human genomics (Nature Methods) Methods, 'Data preparation > Hardware', paragraphs 1 and 2: 'The 500M-parameter models were trained on a single node for a day, whereas the 2.5B-parameter models required the whole cluster for 28 days to be trained.' Version: Nature Methods 22, 287-297 (published online 2024-11-28); PMC11810778 full-text XML | not individually reviewed No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Sources and history
Release 2026-10-22-1b7cf027e4f6 · Record review: source checked
1 source record and release history
- Nucleotide Transformer: building and evaluating robust foundation models for human genomics (Nature Methods) · Original source · Nature Methods 22, 287-297 (published online 2024-11-28); PMC11810778 full-text XML
Technical metadata and extraction receipts
Stable ID: gfm-guide-20261014-claim-nt-training-compute
- field
- training_compute
- value
- All models were trained on Cambridge-1 (16 nodes of eight A100 GPUs, 128 GPUs). The 500M-parameter models trained on one node for a day; the 2.5B-parameter models used the whole cluster for 28 days; NT-v2 models (50M to 500M) trained on one node for a day. Probing embeddings took 2 days on one 8-A100 node, and fitting 760,000 downstream models took 2.5 days on 3,000 CPUs.
- source locator
- Methods, 'Data preparation > Hardware', paragraphs 1 and 2: 'The 500M-parameter models were trained on a single node for a day, whereas the 2.5B-parameter models required the whole cluster for 28 days to be trained.'
- review
- method: source-hash-verification; ai-assisted-source-review; method note: Each source sentence the claim rests on asserted verbatim in the reviewer's own text extraction (review/check_gfm_guide.py); the claim text was then read against them.; reviewer: claude; reviewer note: Independent Claude (Opus 5.5) review agent for PR #150; did not extract this batch; no human review claimed; date: 2026-10-14; artifact sha256: 7c3b78a4f38ef053a08e466222e5662dd9711d91c535512d0b35d459d1fc7249; retrieval url: https://www.ebi.ac.uk/europepmc/webservices/rest/PMC11810778/fullTextXML; note: Claim matches the source.
Related records
- subject: Nucleotide Transformer