Venture StepResearch Note
Foundation Model Pretraining Pipeline Framework
| Stage | Required record | |---|---| | Collection | Source classes, acquisition authority, time range, exclusions, and provenance | | Extraction | Parser, encoding, lang
In this article
Foundation Model Pretraining Pipeline Framework
| Stage | Required record |
|---|---|
| Collection | Source classes, acquisition authority, time range, exclusions, and provenance |
| Extraction | Parser, encoding, language, document boundaries, and failure handling |
| Filtering | Quality, safety, language, domain, code, and classifier rules |
| Deduplication | URL, document, span, line, or semantic method and thresholds |
| Mixture | Categories, weights, sampling, curriculum, and later annealing |
| Tokenization | Tokenizer version, vocabulary, normalization, and language effects |
| Training | Artifact, compute, optimizer, schedule, sequence length, and checkpoints |
| Evaluation | Held-out data, contamination checks, capabilities, safety, and limitations |
A disclosed process does not disclose the full dataset. Public sources may describe methods, categories, proportions, or token counts while withholding exact documents, licenses, removals, and lineage.
Sources
Follow the evidence.
- Introducing Llama 3.1ai.meta.com
- ai.meta.com: the llama 3 herd of modelsai.meta.com
- arxiv.org: 1810arxiv.org
- crfm.stanford.edu: indexcrfm.stanford.edu
- arxiv.org: 2203arxiv.org
- open.spotify.com: 0iRBPcPw9iYjpUVAVWSkRCopen.spotify.com
- NIST AI Risk Management Frameworknist.gov
- github.com: MODEL CARDgithub.com
- daltonanderson.ghost.io: metas llama 3 1 inside the ai research paperdaltonanderson.ghost.io
- Meta Llama models repositorygithub.com
- arxiv.org: 2001arxiv.org
- youtu.be: UMhmWCor1kYyoutu.be
- github.com: LICENSEgithub.com