NLP Lineage

13 March 2023 · Alignment

Alpaca

Stanford Alpaca

R. Taori, I. Gulrajani, T. Zhang, et al.

Date
13 March 2023
What the date marks
Announcement
Kind
Model
Organisation
Stanford CRFM
Access
non-commercial
Threads
In the guided tour
Chapter 8. The weights get out
Learning phases
5. Fine-tuning

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

Read the primary source (crfm.stanford.edu)

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

What it changed

Before it

Instruction tuning was assumed to need industrial resources and proprietary data.

The problem

Could a university group turn a base model into an assistant for pocket change?

What it introduced

52,000 self-instruct examples generated from text-davinci-003, used to fine-tune LLaMA 7B for a few hundred dollars.

Why it matters

It showed capability could be distilled cheaply from a stronger model, which set off the open fine-tune explosion and the licensing fights.

What modern models inherit

Cheap instruction tuning by distilling from a stronger model.

What came next

Vicuna and dozens of derivatives; distillation became standard practice and a terms-of-service problem.

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

Alpaca has 41 documented ancestors across 9 chapters, reaching back to Recurrent networks in 1990. Showing its direct parents and the 18 turning points among them.

Alpaca has 41 documented ancestors across 9 chapters, reaching back to Recurrent networks in 1990. Showing all of them.

Alpaca has 42 recorded ancestors, including indirect ones, across 9 chapters, reaching back to Recurrent networks in 1990. Showing its direct parents and the 18 turning points among them.

Alpaca has 42 recorded ancestors, including indirect ones, across 9 chapters, reaching back to Recurrent networks in 1990. Showing all of them.

  1. 2023AlpacaThis milestone.
  2. 2023LLaMA Turning pointAlpaca built directly on thisChapter 8. The weights get out
  3. 2022Self-InstructAlpaca built directly on thisChapter 6. Teaching models what people want
  4. 2022GPT-3.5 Turning pointAlpaca was influenced by thisChapter 7. The assistant goes public
  5. 2022Chinchilla Turning pointLLaMA built directly on thisChapter 5. Scale becomes a science
  6. 2022InstructGPT Turning pointGPT-3.5 built directly on thisChapter 6. Teaching models what people want
  7. 2021GopherChinchilla built directly on thisChapter 5. Scale becomes a science
  8. 2021FLANSelf-Instruct was influenced by thisChapter 6. Teaching models what people want
  9. 2021RoPE Turning pointLLaMA built directly on thisChapter 10. Reading more than you remember
  10. 2020RLHF for summarisation Turning pointInstructGPT built directly on thisChapter 6. Teaching models what people want
  11. 2020GPT-3 Turning pointGPT-3.5 built directly on this
    Self-Instruct built directly on this    Chapter 5. Scale becomes a science
  12. 2020Scaling laws Turning pointGPT-3 was influenced by this
    Chinchilla built directly on this    Chapter 5. Scale becomes a science
  13. 2019T5 Turning pointFLAN was influenced by thisChapter 4. Pretrain once, use everywhere
  14. 2019C4 Turning pointT5 was influenced by thisChapter 4. Pretrain once, use everywhere
  15. 2019RLHF for LMsRLHF for summarisation built directly on thisChapter 6. Teaching models what people want
  16. 2019Sparse Transformer Turning pointGPT-3 built directly on thisChapter 4. Pretrain once, use everywhere
  17. 2019GPT-2 Turning pointGPT-3 built directly on thisChapter 4. Pretrain once, use everywhere
  18. 2019WebTextGPT-2 was influenced by thisChapter 4. Pretrain once, use everywhere
  19. 2019Transformer-XLRoPE was influenced by thisChapter 4. Pretrain once, use everywhere
  20. 2018BERT Turning pointT5 was influenced by thisChapter 4. Pretrain once, use everywhere
  21. 2018SentencePieceT5 built directly on thisChapter 4. Pretrain once, use everywhere
  22. 2018GPT-1GPT-2 built directly on thisChapter 4. Pretrain once, use everywhere
  23. 2018ELMoBERT was influenced by thisChapter 4. Pretrain once, use everywhere
  24. 2018ULMFiTBERT was influenced by thisChapter 4. Pretrain once, use everywhere
  25. 2017CoVeELMo was influenced by thisChapter 3. Attention, then only attention
  26. 2017Transformer Turning pointRoPE built directly on thisChapter 3. Attention, then only attention
  27. 2017RLHF originRLHF for summarisation built directly on thisChapter 6. Teaching models what people want
  28. 2016Layer normTransformer built directly on this
    GPT-2 built directly on this    Chapter 3. Attention, then only attention
  29. 2015Residual connectionsTransformer was influenced by thisChapter 3. Attention, then only attention
  30. 2015LM pretraining Turning pointBERT was influenced by this
    GPT-1 was influenced by this    Chapter 2. Words become vectors
  31. 2015BPE tokenizationLLaMA built directly on thisChapter 2. Words become vectors
  32. 2015Luong attentionTransformer was influenced by thisChapter 3. Attention, then only attention
  33. 2014AdamTransformer was influenced by thisChapter 2. Words become vectors
  34. 2014GloVeELMo built directly on thisChapter 2. Words become vectors
  35. 2014Seq2seq Turning pointTransformer built directly on thisChapter 2. Words become vectors
  36. 2014Attention Turning pointTransformer built directly on thisChapter 3. Attention, then only attention
  37. 2014GRU / encoder-decoderAttention built directly on thisChapter 2. Words become vectors
  38. 2013word2vecELMo was influenced by thisChapter 2. Words become vectors
  39. 2011NLP from scratchELMo was influenced by thisChapter 1. Language as probability
  40. 2003Neural LMNLP from scratch was influenced by this
    word2vec was influenced by this    Chapter 1. Language as probability
  41. 1997LSTM Turning pointSeq2seq built directly on thisChapter 1. Language as probability
  42. 1990Recurrent networksLSTM was influenced by thisChapter 1. Language as probability
  1. 2023AlpacaThis milestone.
  2. 2023LLaMA Turning pointAlpaca built directly on thisChapter 8. The weights get out
  3. 2022Self-InstructAlpaca built directly on thisChapter 6. Teaching models what people want
  4. 2022GPT-3.5 Turning pointAlpaca was influenced by thisChapter 7. The assistant goes public
  5. 2022Chinchilla Turning pointLLaMA built directly on thisChapter 5. Scale becomes a science
  6. 2022InstructGPT Turning pointGPT-3.5 built directly on thisChapter 6. Teaching models what people want
  7. 2021GopherChinchilla built directly on thisChapter 5. Scale becomes a science
  8. 2021FLANSelf-Instruct was influenced by thisChapter 6. Teaching models what people want
  9. 2021RoPE Turning pointLLaMA built directly on thisChapter 10. Reading more than you remember
  10. 2020RLHF for summarisation Turning pointInstructGPT built directly on thisChapter 6. Teaching models what people want
  11. 2020GPT-3 Turning pointGPT-3.5 built directly on this
    Self-Instruct built directly on this    Chapter 5. Scale becomes a science
  12. 2020Scaling laws Turning pointGPT-3 was influenced by this
    Chinchilla built directly on this    Chapter 5. Scale becomes a science
  13. 2019T5 Turning pointFLAN was influenced by thisChapter 4. Pretrain once, use everywhere
  14. 2019C4 Turning pointT5 was influenced by thisChapter 4. Pretrain once, use everywhere
  15. 2019RLHF for LMsRLHF for summarisation built directly on thisChapter 6. Teaching models what people want
  16. 2019Sparse Transformer Turning pointGPT-3 built directly on thisChapter 4. Pretrain once, use everywhere
  17. 2019GPT-2 Turning pointGPT-3 built directly on thisChapter 4. Pretrain once, use everywhere
  18. 2019WebTextGPT-2 was influenced by thisChapter 4. Pretrain once, use everywhere
  19. 2019Transformer-XLRoPE was influenced by thisChapter 4. Pretrain once, use everywhere
  20. 2018BERT Turning pointT5 was influenced by thisChapter 4. Pretrain once, use everywhere
  21. 2018SentencePieceT5 built directly on thisChapter 4. Pretrain once, use everywhere
  22. 2018GPT-1GPT-2 built directly on thisChapter 4. Pretrain once, use everywhere
  23. 2018ELMoBERT was influenced by this
    GPT-1 was influenced by this (indirect influence)    Chapter 4. Pretrain once, use everywhere
  24. 2018ULMFiTBERT was influenced by this
    GPT-1 was influenced by this (indirect influence)    Chapter 4. Pretrain once, use everywhere
  25. 2017CoVeELMo was influenced by thisChapter 3. Attention, then only attention
  26. 2017Transformer Turning pointRoPE built directly on thisChapter 3. Attention, then only attention
  27. 2017RLHF originRLHF for summarisation built directly on thisChapter 6. Teaching models what people want
  28. 2017ConvS2STransformer was influenced by this (indirect influence)Chapter 3. Attention, then only attention
  29. 2016Layer normTransformer built directly on this
    GPT-2 built directly on this    Chapter 3. Attention, then only attention
  30. 2015Residual connectionsTransformer was influenced by thisChapter 3. Attention, then only attention
  31. 2015LM pretraining Turning pointBERT was influenced by this
    GPT-1 was influenced by this    Chapter 2. Words become vectors
  32. 2015BPE tokenizationLLaMA built directly on thisChapter 2. Words become vectors
  33. 2015Luong attentionTransformer was influenced by thisChapter 3. Attention, then only attention
  34. 2014AdamTransformer was influenced by thisChapter 2. Words become vectors
  35. 2014GloVeELMo built directly on thisChapter 2. Words become vectors
  36. 2014Seq2seq Turning pointTransformer built directly on thisChapter 2. Words become vectors
  37. 2014Attention Turning pointTransformer built directly on thisChapter 3. Attention, then only attention
  38. 2014GRU / encoder-decoderAttention built directly on thisChapter 2. Words become vectors
  39. 2013word2vecELMo was influenced by thisChapter 2. Words become vectors
  40. 2011NLP from scratchELMo was influenced by thisChapter 1. Language as probability
  41. 2003Neural LMNLP from scratch was influenced by this
    word2vec was influenced by this    Chapter 1. Language as probability
  42. 1997LSTM Turning pointSeq2seq built directly on thisChapter 1. Language as probability
  43. 1990Recurrent networksLSTM was influenced by thisChapter 1. Language as probability

After: what it led to

No documented descendants are recorded for Alpaca without weak links.

No documented descendants are recorded for Alpaca without weak links.

No recorded descendants are recorded for Alpaca.

No recorded descendants are recorded for Alpaca.

Direct links and their sources

Where it came from

Built directly on

Influenced by

What it led to

None recorded in the sources used.

Terms