Oxen-AI / mamba-dive
This is the code that went into our practical dive using mamba as information extraction
☆51Updated last year
Alternatives and similar repositories for mamba-dive:
Users that are interested in mamba-dive are comparing it to the libraries listed below
- A single repo with all scripts and utils to train / fine-tune the Mamba model with or without FIM☆50Updated 10 months ago
- Collection of autoregressive model implementation☆81Updated this week
- ☆43Updated 3 months ago
- The simplest, fastest repository for training/finetuning medium-sized xLSTMs.☆39Updated 8 months ago
- Set of scripts to finetune LLMs☆36Updated 10 months ago
- ☆80Updated 3 weeks ago
- ☆32Updated last year
- A repository for research on medium sized language models.☆76Updated 8 months ago
- ☆78Updated 10 months ago
- Evaluating the Mamba architecture on the Othello game☆44Updated 9 months ago
- ☆71Updated 5 months ago
- Implementation of the Mamba SSM with hf_integration.☆56Updated 5 months ago
- GoldFinch and other hybrid transformer components☆43Updated 6 months ago
- My Implementation of Q-Sparse: All Large Language Models can be Fully Sparsely-Activated☆31Updated 6 months ago
- ☆48Updated 3 months ago
- ☆47Updated 5 months ago
- Spherical Merge Pytorch/HF format Language Models with minimal feature loss.☆115Updated last year
- My fork os allen AI's OLMo for educational purposes.☆30Updated 2 months ago
- Official repository for the paper "Approximating Two-Layer Feedforward Networks for Efficient Transformers"☆36Updated last year
- Yet another random morning idea to be quickly tried and architecture shared if it works; to allow the transformer to pause for any amount…☆53Updated last year
- Implementation of GateLoop Transformer in Pytorch and Jax☆87Updated 7 months ago
- Small and Efficient Mathematical Reasoning LLMs☆71Updated last year
- RWKV, in easy to read code☆65Updated 2 months ago
- ☆87Updated last year
- Explorations into the proposal from the paper "Grokfast, Accelerated Grokking by Amplifying Slow Gradients"☆95Updated last month
- ☆112Updated 4 months ago
- Pytorch implementation of the PEER block from the paper, Mixture of A Million Experts, by Xu Owen He at Deepmind☆117Updated 5 months ago
- One Initialization to Rule them All: Fine-tuning via Explained Variance Adaptation☆36Updated 4 months ago
- Token Omission Via Attention☆122Updated 4 months ago
- Repo hosting codes and materials related to speeding LLMs' inference using token merging.☆35Updated 9 months ago