Goals: Add links that are reasonable and good explanations of how stuff works. No hype and no vendor content if possible. Practical first-hand accounts of models in prod eagerly sought.
import torch | |
from huggingface_hub import hf_hub_download | |
from diffusers import FluxTransformer2DModel, DiffusionPipeline | |
dtype, device = torch.bfloat16, "cuda" | |
ckpt_id = "black-forest-labs/FLUX.1-schnell" | |
with torch.device("meta"): | |
config = FluxTransformer2DModel.load_config(ckpt_id, subfolder="transformer") | |
model = FluxTransformer2DModel.from_config(config).to(dtype) |
ChatGPT appeared like an explosion on all my social media timelines in early December 2022. While I keep up with machine learning as an industry, I wasn't focused so much on this particular corner, and all the screenshots seemed like they came out of nowhere. What was this model? How did the chat prompting work? What was the context of OpenAI doing this work and collecting my prompts for training data?
I decided to do a quick investigation. Here's all the information I've found so far. I'm aggregating and synthesizing it as I go, so it's currently changing pretty frequently.
I have an updated version of this on my blog here: https://chrisamico.com/blog/2023-01-14/python-setup/.
This is my recommended Python setup, as of Fall 2022. The Python landscape can be a confusing mess of overlapping tools that sometimes don't work well together. This is an effort to standardize our approach and environments.
- Python docs: https://docs.python.org/3/
- Python Standard Library: - Start here when you're trying to solve a specific problem
#!/usr/bin/env bash | |
for f in $(<~/git/repos); do | |
cd ~/git/$f | |
git pull > /dev/null & | |
cd - > /dev/null | |
done | |
wait < <(jobs -p) | |
for f in $(<~/git/repos); do |
I've been asked by several people over time about my experience with the classes offered by Bradfield, and thought that I should save some future keystrokes by writing up a short gist for future reference. Hopefully this gist will be useful for others who are considering Bradfield and wondering it is worth it. My intended audience is primarily Launch School students who have completed the Core program and likely also Capstone, but the majority of this gist will be applicable to anyone who is a working/experienced software engineer.
Since late 2019, I've taken 4 short courses from the Bradfield School of Computer Science and in 2021 I enrolled in their Computer Science Intensive (CSI) program1. Overall, I've found the courses and CSI to be an excellent opportunity to grown my technical skills and broaden my knowledge of CS topics.
The courses I completed were:
- Computer Architecture: The Hardware/Software Interface
Rank | Type | Prefix/Suffix | Length | |
---|---|---|---|---|
1 | Prefix | my+ | 2 | |
2 | Suffix | +online | 6 | |
3 | Prefix | the+ | 3 | |
4 | Suffix | +web | 3 | |
5 | Suffix | +media | 5 | |
6 | Prefix | web+ | 3 | |
7 | Suffix | +world | 5 | |
8 | Suffix | +net | 3 | |
9 | Prefix | go+ | 2 |
default['sshd']['sshd_config']['AuthenticationMethods'] = 'publickey,keyboard-interactive:pam' | |
default['sshd']['sshd_config']['ChallengeResponseAuthentication'] = 'yes' | |
default['sshd']['sshd_config']['PasswordAuthentication'] = 'no' |
class Book < Airrecord::Table | |
class Endorser < Airrecord::Table | |
self.base_key = "" | |
self.table_name = "Endorser" | |
end | |
self.base_key = "" | |
self.table_name = "Books" | |
has_many :endorsements, class: 'Book::Endorser', column: 'Endorsements' |