This worked on 14/May/23. The instructions will probably require updating in the future.
llama is a text prediction model similar to GPT-2, and the version of GPT-3 that has not been fine tuned yet. It is also possible to run fine tuned versions (like alpaca or vicuna with this. I think. Those versions are more focused on answering questions)
Note: I have been told that this does not support multiple GPUs. It can only use a single GPU.
It is possible to run LLama 13B with a 6GB graphics card now! (e.g. a RTX 2060). Thanks to the amazing work involved in llama.cpp. The latest change is CUDA/cuBLAS which allows you pick an arbitrary number of the transformer layers to be run on the GPU. This is perfect for low VRAM.
- Clone llama.cpp from git, I am on commit
08737ef720f0510c7ec2aa84d7f70c691073c35d
.
Github.com ui .currently does not natively supoport search for multiple topic tags as of now. However their api allows you to query multiple tags. Below is a simple example to query github.com with ecs and go topic tags. | |
curl -H "Accept: application/vnd.github.mercy-preview+json" \ | |
https://api.github.com/search/repositories?q=topic:ecs+topic:go | |
Response from the github can be rather verbose so lets filter only relavant info such repo url and description. | |
curl -H "Accept: application/vnd.github.mercy-preview+json" \ | |
https://api.github.com/search/repositories\?q\=topic:ecs+topic:go | jq '.items[] | {url:.url, description:.description}' |
This is inspired by A half-hour to learn Rust and Zig in 30 minutes.
Your first Go program as a classical "Hello World" is pretty simple:
First we create a workspace for our project:
class Spiderman { | |
lookOut() { | |
alert('My Spider-Sense is tingling.'); | |
} | |
} | |
let miles = new Spiderman(); | |
miles.lookOut(); |
#!/bin/bash | |
remote=origin ; for brname in `git branch -r | grep $remote | grep -v /master | grep -v /HEAD | awk '{gsub(/^[^\/]+\//,"",$1); print $1}'`; do git branch --track $brname $remote/$brname || true; done 2>/dev/null |
AWS Textract is now out of closed beta. You can read the features page here, and you can also read about its limits here (e.g. no handwriting). Basically, if you've ever had to deal with the hell of getting structured data out of a PDF (scanned image or not), Textract is aiming for your business:
This short gist contains some of my brief observations about Textract and its demo, as well as direct links to the most relevant and important files, such as the Textract demo sample image and the resulting data files from Textract's API. If you have an AWS account, I h
import { onError } from 'apollo-link-error'; | |
import { Observable } from 'apollo-link'; | |
import { buildAuthHeader } from 'utils/requests'; | |
import { getProvider as getGlobalProvider } from 'GlobalState'; | |
let isFetchingToken = false; | |
let tokenSubscribers = []; | |
function subscribeTokenRefresh(cb) { | |
tokenSubscribers.push(cb); |
Node/Express/REST/Promises/Mocha/Chai
- 01: Node Express Basics:
- 02: Express Middleware:
- 03: RESTful and Express Routers:
- 04: Promises:
- 05: Testing with Mocha Chai:
PostgreSQL and KNEX