Transformer Alternatives (mostly SSMs)

• GitHub - sustcsonglin/flash-linear-attention: Efficient implementations of state-of-the-art linear attention models in Pytorch and Triton

• retnet

• GitHub - BlinkDL/RWKV-LM: RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it’s combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, “infinite” ctx_len, and free sentence embedding.

  • GitHub - BlinkDL/ChatRWKV: ChatRWKV is like ChatGPT but powered by RWKV (100% RNN) language model, and open source.

• [2306.11197] Sparse Modular Activation for Efficient Sequence Modeling

• GitHub - renll/SeqBoat: [NeurIPS 2023] Sparse Modular Activation for Efficient Sequence Modeling

Architectures

RWKV

• RWKV-LM/RWKV-v7 at main · BlinkDL/RWKV-LM · GitHub

Monarch Mixer

Making Foundation Models More Efficient - Dan Fu | Stanford MLSys #86 - YouTube

Mamba

• Mamba: The Hard Way

Mamba2

Codestral Mamba (Mistral)

H3

Zamba

Zamba2

• Zyphra

YouTube

Jamba

Samba

• GitHub - microsoft/Samba: Official implementation of “Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language Modeling”

minGRU and minLSTM

• [2410.01201] Were RNNs All We Needed?

xLSTM

Hawk and Griffin

• Fetching Title#mdig
• https://www.youtube.com/watch?v=0Yi3yUjB-3M&list=PPSV

DeltaNet

DeltaNet

Gated DeltaNets

• [2412.06464] Gated Delta Networks: Improving Mamba2 with Delta Rule
• GitHub - NVlabs/GatedDeltaNet: Official PyTorch Implementation of Gated Delta Networks: Improving Mamba2 with Delta Rule

Hymba

• [2411.13676] Hymba: A Hybrid-head Architecture for Small Language Models nvidia/Hymba-1.5B-Base · Hugging Face

• modeling_hymba.py · nvidia/Hymba-1.5B-Base at main

• claims parallel heads work better than stacking
• adds register tokens (128)
  • [ ]
• uses KV cache sharing across layers

Attamba

• [2411.17685] Attamba: Attending To Multi-Token States

Bamba

• GitHub - foundation-model-stack/bamba: Train, tune, and infer Bamba model

Patterns

Hybrids

Pruning

Simba (Hierarchical SSM Pruning)

• Sparsified State-Space Models are Efficient Highway Networks