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CS336: Language Modeling from Scratch (cs336.stanford.edu)

558 points by kristianpaul · 42 days ago · 51 comments on HN

Article summary

The article presents the coursework and schedule for CS336: Language Modeling from Scratch, a Stanford course that focuses on developing language models from scratch. The course covers topics such as data collection, transformer model construction, and model training, and requires proficiency in Python, deep learning, and systems optimization. The course staff provides resources and guidance for students, including office hours, YouTube lectures, and a Slack channel for discussion. The course also has a honor code that prohibits the use of AI tools to directly solve problems.

Main themes

  • Language Modeling
  • Deep Learning
  • Coursework
  • GPU Computing
  • Self-Study
  • Honor Code

What commenters say

  • The course's requirements and resources are sufficient for students to learn and complete the assignments, but some students may need to invest significant time and effort to keep up.
  • The use of GPU computing is not strictly necessary for the course, and students can complete assignments with lower-end GPUs or even CPUs, but may encounter memory and performance issues.
  • The honor code is necessary to ensure that students learn and understand the material, rather than relying on AI tools to complete assignments, but some students may find it challenging to adhere to the code.
  • The course's focus on implementation and hands-on experience is valuable, but some students may prefer a more theoretical or casual approach to learning about language models.
  • The cost of renting GPUs for the course is a significant concern for some students, but others believe it is a worthwhile investment for the learning experience.
  • The course's resources and guidance are helpful, but some students may still encounter difficulties and frustrations, particularly with memory management and troubleshooting.
  • The course's emphasis on community and discussion is important, and some students are interested in forming study groups or online communities to support each other in learning the material.
  • The course's prerequisites, such as machine learning and deep learning, are essential for success, and students who lack these prerequisites may struggle to keep up with the coursework.