Post #2240

‌Hugging Face (Twitter) RT @RisingSayak: Some notes on what someone can do for building chops in ML x open source x modeling: • Take a popular pre-trained model implementation, profile it, spot the bottlenecks, & try to improve its speed-memory trade-off -- it's a valuable skill that any sane hiring manager should understand and credit (they are probably not legit if they don't). is a good example of this. • GPUs are in short supply. So, try reimplementing it in JAX, leveraging its strengths. Make it run on TPUs, blazing fast 🔥 -- this will help you establish that you care about performance and are comfortable switching stacks when needed. https://github.com/sanchit-gandhi/whisper-jax is an amazing example of this. • In the context of an organization, communication is the key. Make sure you document your experience in an easily digestible way so most folks would understand what you achieved. Provide numbers on benchmarks, mention assumptions, and whatever limitations you faced and how you approached them. • Get a pro subscription to whatever AI coding assistant you think works the best for your stuff. Make it a part of your workflow, but DO NOT become overly reliant on it. Have enough juice in the process so that you can build muscle memory and objective evidence of your intellect over time. • Have fun! It gives me a sense of joy and relief to know that back in the days, we did all of it happily WITHOUT any AI coding assistance. Lots of fun, despair, and anxiety -- but all worth it; 10/10 -- would do it again!