v0.5.0

This release brings two new features:

Top-K Transcoders

• Top-K transcoders are now supported - thanks to @zsquaredz for helping with this! This means that these Llama-3 8B Instruct transcoders are now usable.
• In the config.yaml, specify activation: topk to mark the transcoders as top-k transcoders, and use k: 128 to indicate the value of k (e.g., 128). The weight files for these transcoders should be the same as e.g. relu transcoders.
• load_relu_transcoder is now load_transcoder, and serves as a general function for loading per-layer transcoders. It acts the same as the old load_relu_transcoder, except that you can now pass in the activation_fn that you want used.

Local Features

• Thanks to @s-ewbank, there is now a features_dir argument for serve and circuit-tracer start-server that allows you to specify a local directory where locally-computed features live! This is helpful if you've trained your own transcoders / computed your own features, and don't wish to upload them to Huggingface.