6/23/23: Hugging Face again

  Machine Learning Study Group

Welcome! We start at 4:00. Zoom automatically ends the meeting after 40 minutes. New members are always welcome and anyone can join. You may attend any or all sessions. Also feel free to ask to be removed from the invite list at any time, as we have no wish to send unneeded emails which we all certainly get too many of.

 

Agenda & Minutes

• Welcome to the 68th meeting, June 23, 2023.
• Status updates/news/inputs/comments
• Student and project updates?
• SR can present his own work next week
  
• Any other updates/news/inputs or comments?

• Today is week 2 of a new 3-week cycle of: background reading one week, Huggingface prep/discuss the next week, and lab exercise in the 3rd week. No one is really needed to "lead," we think/hope.
  
• Our last background reading session (last week, week 1 of the 3-week cycle) was from https://openai.com/research/gpt-4 about GPT-4. We got up to the section "Predictable scaling." We proceeded from there today and got up to the section "API."
• To continue with the Huggingface lab program, last time we worked on this (2 weeks ago), we reviewed https://huggingface.co/learn/nlp-course/chapter0/1?fw=tf using Colab. Then we started on chapter 1, https://huggingface.co/learn/nlp-course/chapter1/1?fw=tf, and got through the initial video. Today, we finished that page, clicked "next" to go to https://huggingface.co/learn/nlp-course/chapter1/2?fw=tf and read that, then "next" again to go to part 3, https://huggingface.co/learn/nlp-course/chapter1/3?fw=tf, read the first paragraph and went to the collab link where we worked through that through the code window
  
  classifier(

      ["I've been waiting for a HuggingFace course my whole life.", "I hate this so much!"]

  )
  Next time we work on this we could start right after that.
  
• Here are some other things we could choose to read from in the future.
  
• At some point we can discuss and vote on other sources. See the list on the page of sources. Also Youtube is full of videos about neural nets, transformers, etc.
• MC suggested: Sparks of Artificial General Intelligence: Early experiments with GPT-4 (https://arxiv.org/abs/2303.12712). We read the abstract to decide whether to read the article. The group's evaluation was 3 6/7 out of 5 to read it.

• Readings/videos/demos we have finished. 
• 2/17/23; "Deep Learning for AI" by Bengio, LeCun and Hinton, the Turing Award Lecture paper for 2018, published in CACM, 2021, https://dl.acm.org/doi/pdf/10.1145/3448250.
  
• ChatGPT Is a Tipping Point for AI (Harvard Business Review). Finished 1/27/23.
• 12/16/22: We demoed ChatGPT.
• 11/4/22: We viewed and discussed a transformers video: https://www.youtube.com/watch?v=TQQlZhbC5ps first. This seemed to be one of the better videos of the many out there.
• Transformers From Scratch," https://e2eml.school/transformers.html. Finished on 10/28/22.
• The Narrated Transformer Language Model, Jay Alammar, https://www.youtube.com/watch?v=-QH8fRhqFHM, finished 7/22/22.
• https://www.youtube.com/watch?v=F1X4fHzF4mQ. Finished 8/26/22.
  
• We also finished other things from before this list of finished sources was created to keep a record of them.