NLP Lineage

11 July 2022 · Language modelling

BLOOM

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

BigScience (Scao et al., 1000+ contributors)

Date
11 July 2022
What the date marks
Model release
Kind
Model
Organisation
BigScience / Hugging Face
Access
BLOOM RAIL v1.0
Other dates
paper 2022-11-09
Threads
In the guided tour
Chapter 8. The weights get out
Learning phases
2. How LLMs are trained; 8. Training from scratch

Notable: no later milestone in the data is documented as descending from it. How levels are decided

Read the primary source (huggingface.co)

Full summary in progress. Until then, this page shows the milestone's record from the research data.

What it changed

Before it

Large models were built inside single companies and released, if at all, on their terms.

The problem

No model of that scale had been built by an open scientific collaboration, and none covered many languages well.

What it introduced

A 176B multilingual model trained in public by a thousand researchers on a national supercomputer, released with a responsible-use licence.

Why it matters

It proved a large model could be built as open science, and put multilingual coverage on the agenda.

What modern models inherit

Open collaborative training, and the idea of use-restricted rather than fully free licences.

What came next

The RAIL licence influenced later custom licences; the collaboration model informed open data efforts.

Before and after

The milestones it descends from, and the milestones that descend from it. Work developed alongside it is not counted. Weak links are left out unless you include them.

Before: where it came from

BLOOM has 22 documented ancestors across 6 chapters, reaching back to Recurrent networks in 1990. Showing its direct parents and the 10 turning points among them.

BLOOM has 22 documented ancestors across 6 chapters, reaching back to Recurrent networks in 1990. Showing all of them.

BLOOM has 31 recorded ancestors, including indirect ones, across 6 chapters, reaching back to Recurrent networks in 1990. Showing its direct parents and the 10 turning points among them.

BLOOM has 31 recorded ancestors, including indirect ones, across 6 chapters, reaching back to Recurrent networks in 1990. Showing all of them.

  1. 2022BLOOMThis milestone.
  2. 2021ALiBiBLOOM built directly on thisChapter 10. Reading more than you remember
  3. 2020The PileBLOOM was influenced by thisChapter 5. Scale becomes a science
  4. 2020GPT-3 Turning pointThe Pile was influenced by thisChapter 5. Scale becomes a science
  5. 2020Scaling laws Turning pointGPT-3 was influenced by thisChapter 5. Scale becomes a science
  6. 2019C4 Turning pointThe Pile was influenced by thisChapter 4. Pretrain once, use everywhere
  7. 2019ZeRO / DeepSpeedBLOOM was influenced by thisChapter 4. Pretrain once, use everywhere
  8. 2019Sparse Transformer Turning pointGPT-3 built directly on thisChapter 4. Pretrain once, use everywhere
  9. 2019GPT-2 Turning pointGPT-3 built directly on thisChapter 4. Pretrain once, use everywhere
  10. 2019WebTextGPT-2 was influenced by thisChapter 4. Pretrain once, use everywhere
  11. 2018GPT-1GPT-2 built directly on thisChapter 4. Pretrain once, use everywhere
  12. 2017Transformer Turning pointALiBi built directly on thisChapter 3. Attention, then only attention
  13. 2016Layer normTransformer built directly on thisChapter 3. Attention, then only attention
  14. 2015Residual connectionsTransformer was influenced by thisChapter 3. Attention, then only attention
  15. 2015LM pretraining Turning pointGPT-1 was influenced by thisChapter 2. Words become vectors
  16. 2015BPE tokenizationGPT-2 built directly on thisChapter 2. Words become vectors
  17. 2015Luong attentionTransformer was influenced by thisChapter 3. Attention, then only attention
  18. 2014AdamZeRO / DeepSpeed built directly on thisChapter 2. Words become vectors
  19. 2014Seq2seq Turning pointTransformer built directly on thisChapter 2. Words become vectors
  20. 2014Attention Turning pointTransformer built directly on thisChapter 3. Attention, then only attention
  21. 2014GRU / encoder-decoderAttention built directly on thisChapter 2. Words become vectors
  22. 1997LSTM Turning pointSeq2seq built directly on thisChapter 1. Language as probability
  23. 1990Recurrent networksLSTM was influenced by thisChapter 1. Language as probability
  1. 2022BLOOMThis milestone.
  2. 2021ALiBiBLOOM built directly on thisChapter 10. Reading more than you remember
  3. 2020The PileBLOOM was influenced by thisChapter 5. Scale becomes a science
  4. 2020GPT-3 Turning pointThe Pile was influenced by thisChapter 5. Scale becomes a science
  5. 2020Scaling laws Turning pointGPT-3 was influenced by thisChapter 5. Scale becomes a science
  6. 2019C4 Turning pointThe Pile was influenced by thisChapter 4. Pretrain once, use everywhere
  7. 2019ZeRO / DeepSpeedBLOOM was influenced by thisChapter 4. Pretrain once, use everywhere
  8. 2019Sparse Transformer Turning pointGPT-3 built directly on thisChapter 4. Pretrain once, use everywhere
  9. 2019GPT-2 Turning pointGPT-3 built directly on thisChapter 4. Pretrain once, use everywhere
  10. 2019WebTextC4 was influenced by this (indirect influence)Chapter 4. Pretrain once, use everywhere
  11. 2019Transformer-XLSparse Transformer was influenced by this (indirect influence)Chapter 4. Pretrain once, use everywhere
  12. 2018GPT-1GPT-2 built directly on this
    WebText was influenced by this    Chapter 4. Pretrain once, use everywhere
  13. 2018ELMoGPT-1 was influenced by this (indirect influence)Chapter 4. Pretrain once, use everywhere
  14. 2018ULMFiTGPT-1 was influenced by this (indirect influence)Chapter 4. Pretrain once, use everywhere
  15. 2017CoVeELMo was influenced by thisChapter 3. Attention, then only attention
  16. 2017Transformer Turning pointALiBi built directly on thisChapter 3. Attention, then only attention
  17. 2017ConvS2STransformer was influenced by this (indirect influence)Chapter 3. Attention, then only attention
  18. 2016Layer normTransformer built directly on thisChapter 3. Attention, then only attention
  19. 2015Residual connectionsTransformer was influenced by thisChapter 3. Attention, then only attention
  20. 2015LM pretraining Turning pointGPT-1 was influenced by thisChapter 2. Words become vectors
  21. 2015BPE tokenizationGPT-2 built directly on thisChapter 2. Words become vectors
  22. 2015Luong attentionTransformer was influenced by thisChapter 3. Attention, then only attention
  23. 2014AdamZeRO / DeepSpeed built directly on thisChapter 2. Words become vectors
  24. 2014GloVeELMo built directly on thisChapter 2. Words become vectors
  25. 2014Seq2seq Turning pointTransformer built directly on thisChapter 2. Words become vectors
  26. 2014Attention Turning pointTransformer built directly on thisChapter 3. Attention, then only attention
  27. 2014GRU / encoder-decoderAttention built directly on thisChapter 2. Words become vectors
  28. 2013word2vecELMo was influenced by thisChapter 2. Words become vectors
  29. 2011NLP from scratchELMo was influenced by thisChapter 1. Language as probability
  30. 2003Neural LMNLP from scratch was influenced by this
    word2vec was influenced by this    Chapter 1. Language as probability
  31. 1997LSTM Turning pointSeq2seq built directly on thisChapter 1. Language as probability
  32. 1990Recurrent networksLSTM was influenced by thisChapter 1. Language as probability

After: what it led to

No documented descendants are recorded for BLOOM without weak links.

No documented descendants are recorded for BLOOM without weak links.

No recorded descendants are recorded for BLOOM.

No recorded descendants are recorded for BLOOM.

Direct links and their sources

Where it came from

Built directly on

Influenced by

Developed alongside

What it led to

None recorded in the sources used.

Terms