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Hi there!
Could you please provide instructions on how to reproduce the training with auto-encoder?
As I try to run the code with,
```
python3 big_sweep_experiments.py
```
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It first …
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### Suggestion / Feature Request
Been curious for awhile now, then moreso since reading Disentangling Dense Embeddings with Sparse Autoencoders (https://arxiv.org/html/2408.00657v2)
It looks like …
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# Sparse Autoencoders for a More Interpretable RLHF | Naomi Bashkansky
Extending Anthropic's recent monosemanticity results toward a new, more interpretable way to fine-tune.
[https://naomibashkansk…
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Exciting work. Love it that you are exploring autoencoders.
I wish this works similarly well with sparse autoencoders, hence the title of the issue.
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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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We could support dimensionality reduction through autoencoders. Here's a useful looking tutorial (it looks relatively straightforward to implement all of the variants in the tutorial): https://blog.k…
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Sparse autoencoder is an autoencoder with additional constraint that most coefficients tend to be zero, as described here: http://deeplearning.stanford.edu/wiki/index.php/Autoencoders_and_Sparsity
I…
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Suggested list of courses would be:
- An introduction to deep learning **
- How to train a neural network
- Regularisation in neural networks
- Deep Bayesian neural networks
- Conv…
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I meet OOM problem in refining, Here is my detailed error:
Refining...: 0%| | …
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Hi Team,
Firstly I want to say thank you so much for implementing a truly model-agnostic method for counterfactuals! I've been searching for many months now for a counterfactual tool I can easily …