name: tufte-viz description: | Ideate and critique data visualizations using Edward Tufte's principles from "The Visual Display of Quantitative Information." Use this skill when: (1) Designing new data visualizations or charts (2) Critiquing or improving existing visualizations (3) Reviewing dashboards or reports for graphical integrity (4) Deciding between visualization approaches (5) Reducing chartjunk or improving data-ink ratio (6) Planning small multiples or high-density displays
Yoav Goldberg, April 2023.
With the release of the ChatGPT model and followup large language models (LLMs), there was a lot of discussion of the importance of "RLHF training", that is, "reinforcement learning from human feedback". I was puzzled for a while as to why RL (Reinforcement Learning) is better than learning from demonstrations (a.k.a supervised learning) for training language models. Shouldn't learning from demonstrations (or, in language model terminology "instruction fine tuning", learning to immitate human written answers) be sufficient? I came up with a theoretical argument that was somewhat convincing. But I came to realize there is an additional argumment which not only supports the case of RL training, but also requires it, in particular for models like ChatGPT. This additional argument is spelled out in (the first half of) a talk by John Schulman from OpenAI. This post pretty much
| type ProjectId = string; // eg: 2a13b3e1-7a74-3b2b-9758-1b398845a8e8 | |
| type UserId = number; | |
| type ShareId = string; | |
| type ClientId = string; | |
| // login | |
| // response sessionid returned in set-cookie | |
| // curl -X POST https://workflowy.com/accounts/login/ -F 'username=<username>' -F'password=<password>' -H 'accept: application/json' -D - | |
| export interface LoginFormData { | |
| username: string; |
The repository for the assignment is public and Github does not allow the creation of private forks for public repositories.
The correct way of creating a private frok by duplicating the repo is documented here.
For this assignment the commands are:
- Create a bare clone of the repository.
(This is temporary and will be removed so just do it wherever.)
git clone --bare git@github.com:usi-systems/easytrace.git
To remove a submodule you need to:
- Delete the relevant section from the .gitmodules file.
- Stage the .gitmodules changes git add .gitmodules
- Delete the relevant section from .git/config.
- Run git rm --cached path_to_submodule (no trailing slash).
- Run rm -rf .git/modules/path_to_submodule (no trailing slash).
- Commit git commit -m "Removed submodule "
- Delete the now untracked submodule files rm -rf path_to_submodule
| # Generate PDFs from the Markdown source files | |
| # | |
| # In order to use this makefile, you need some tools: | |
| # - GNU make | |
| # - Pandoc | |
| # - LuaLaTeX | |
| # - DejaVu Sans fonts | |
| # Directory containing source (Markdown) files | |
| source := src |
