|
--- |
|
base_model: EleutherAI/pythia-160m-deduped |
|
language: en |
|
library_name: mlsae |
|
license: mit |
|
tags: |
|
- arxiv:2409.04185 |
|
- model_hub_mixin |
|
- pytorch_model_hub_mixin |
|
--- |
|
|
|
# Model Card for tim-lawson/mlsae-pythia-160m-deduped-x64-k512-tfm |
|
|
|
A Multi-Layer Sparse Autoencoder (MLSAE) trained on the residual stream activation |
|
vectors from [EleutherAI/pythia-160m-deduped](https://huggingface.co/EleutherAI/pythia-160m-deduped) with an |
|
expansion factor of R = 64 and sparsity k = 512, over 1 billion |
|
tokens from [monology/pile-uncopyrighted](https://huggingface.co/datasets/monology/pile-uncopyrighted). |
|
|
|
|
|
This model is a PyTorch Lightning MLSAETransformer module, which includes the underlying |
|
transformer. |
|
|
|
|
|
### Model Sources |
|
|
|
- **Repository:** <https://github.com/tim-lawson/mlsae> |
|
- **Paper:** <https://arxiv.org/abs/2409.04185> |
|
- **Weights & Biases:** <https://wandb.ai/timlawson-/mlsae> |
|
|
|
## Citation |
|
|
|
**BibTeX:** |
|
|
|
```bibtex |
|
@misc{lawson_residual_2024, |
|
title = {Residual {{Stream Analysis}} with {{Multi-Layer SAEs}}}, |
|
author = {Lawson, Tim and Farnik, Lucy and Houghton, Conor and Aitchison, Laurence}, |
|
year = {2024}, |
|
month = oct, |
|
number = {arXiv:2409.04185}, |
|
eprint = {2409.04185}, |
|
primaryclass = {cs}, |
|
publisher = {arXiv}, |
|
doi = {10.48550/arXiv.2409.04185}, |
|
urldate = {2024-10-08}, |
|
archiveprefix = {arXiv} |
|
} |
|
``` |
