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Nick Wall


/ 1 min read

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What is Menagerie?

Menagerie is a collection of models and techniques I find interesting. It is similar to scratch but more focused on quick exploration rather than well designed and readable implementations.

Current Exhibits

  • QLoRA Supervised Fine Tuning of gemma-2b (chat tuned on OpenHermes) for contextual SQL-qa. This is an ongoing experiment as I am working on dynamic statistics retrieval in hooper.
  • An extremely optimized ResNet training implementation using PyTorch. I am still working on this as I want to try to compete with the MLPerf record.
  • Transformer pretraining on the CodeParrot dataset. This implementation trains a tiny model but trains it to be good for its class and uses the new PyTorch Lightning Fabric api as I explore how it fares.

What am I working on?

Menagerie is a playground for me and I am experimenting with many things. Lately I have been working on extending Llama 3’s context length (why was it so small at release Meta???) and model merging. I want to release a better version of some of my VLM experiments with something that could be competitive with some of the top VLMs.