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Is this out of scope? I hope not, would be nice to have a one-stop shop for interpretability tooling.
### Proposal
It should be easy to get the most bare-bones interpretability research off the…
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### Proposal
Add support for TracrBench transformers
### Motivation
I and @JeremyAlain recently wrote a paper in which we introduced a dataset of 121 tracr-transformers. Tracr transformers a…
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Hi! Is there an established way to get mamba interpretability, smth similar to self-attention analysis in transformers. Thank you!
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- https://arxiv.org/abs/2106.12620
- 2021
自己注意に基づくモデルであるトランスフォーマーは、近年、コンピュータビジョンの分野で主要なバックボーンとなりつつあります。
しかし、様々なビジョンタスクにおいてトランスフォーマーは目覚ましい成功を収めているにもかかわらず、トランスフォーマーは重い計算と集中的なメモリコストに悩まされている。
この問題を…
e4exp updated
3 years ago
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Hi, I noticed that you submitted a paper titled “Masked Attention as a Mechanism for Improving Interpretability of Vision Transformers” to Medical Imaging with Deep Learning 2024. Do you plan to integ…
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### Model description
https://github.com/noanabeshima/tiny_model
It's a small language model trained on TinyStories for interpretability with sparse autoencoders and transcoders added. It has no…
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# Challenge 22 - XAI for Weather Forecasting Models (Transformer Embeddings)
> **Stream 2 - Machine Learning for Earth Sciences applications**
### Goal
Welcome to the XAI Transformer Embedding …
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**Short Description**
> Transformer Debugger (TDB) is a tool developed by OpenAI's [Superalignment team](https://openai.com/blog/introducing-superalignment) with the goal of supporting investigatio…
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Hello,
The implementation for the Reformer model allows for the reconstruction of the full attention matrix (https://github.com/lucidrains/reformer-pytorch#research). There, the Recorder class can …
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Thanks for your nice contribution!!
When I try to replace the Transformer block in a model with VSSEncoder（The Transformer includes factorized self-attention for its linear complexity as done in…