README.md

voltronformers

Assembling the best SotA AI techniques into a unified model

- 13B parameter BitNet + infini-Attention + DenseFormer + MoD + 
  In Context-Pretraining + 2 stage pretraining 
- upcycle w c-BTX to an 8 expert sparse MoE + MoA 

https://twitter.com/winglian/status/1778675583817326842

References

BitNet

BitNet: Scaling 1-bit Transformers for Large Language Models

• arXiv: https://arxiv.org/abs/2310.11453
• reference implementations:
  • https://github.com/kyegomez/BitNet
  • https://github.com/cg123/bitnet/tree/main

DenseFormer

DenseFormer: Enhancing Information Flow in Transformers via Depth Weighted Averaging

• arXiv: https://arxiv.org/abs/2402.02622
• reference implementations:
  • https://github.com/epfml/DenseFormer/tree/main

Mixture-of-Depths

Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

• arXiv: https://arxiv.org/abs/2404.02258
• reference implementations:
  • https://github.com/thepowerfuldeez/OLMo/blob/80be1a3ff1d4a80167b37a1d97509cc0b54d821d/olmo/mod.py

In-Context Pretraining

In-Context Pretraining: Language Modeling Beyond Document Boundaries

• arXiv: https://arxiv.org/abs/2310.10638

MiniCPM (Two Stage Pre-training Strategy)

MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies

• arXiv: https://arxiv.org/abs/2404.06395

Cluster-Branch-Train-Merge (c-BTM)

Scaling Expert Language Models with Unsupervised Domain Discovery

• arXiv: https://arxiv.org/abs/2303.14177
• reference implementations:
  • https://github.com/kernelmachine/cbtm

Branch-Train-MiX (BTX)

Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM

• arXiv: https://arxiv.org/abs/2403.07816

Mixture Of Attention Heads

Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM

• arXiv: https://arxiv.org/abs/2403.07816
• reference implementations:
  • https://github.com/lucidrains/mixture-of-attention
  • https://github.com/yikangshen/MoA
  • JetMoE: https://arxiv.org/pdf/2404.07413.pdf
• errata:
  • https://twitter.com/Yikang_Shen/status/1777029389638647950