ZekiJohn

Thanks everyone for commenting/contributing! I made this in college for a class and I no longer really use the technology. I encourage you all to help each other, but I probably won't be answering questions anymore.

This article is also on my blog: https://emilykauffman.com/blog/install-anaconda-on-wsl

Note: $ denotes the start of a command. Don't actually type this.

Steps to Install Anaconda on Windows Ubuntu Terminal

1. Install WSL (Ubuntu for Windows - can be found in Windows Store). I recommend the latest version (I'm using 18.04) because there are some bugs they worked out during 14/16 (microsoft/WSL#785)
2. Go to https://repo.continuum.io/archive to find the list of Anaconda releases
3. Select the release you want. I have a 64-bit computer, so I chose the latest release ending in x86_64.sh. If I had a 32-bit computer, I'd select the x86.sh version. If you accidentally try to install the wrong one, you'll get a warning in the terminal. I chose `Anaconda3-5.2.0-Li

rain-1

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.

hwchase17

# STEP 1: Load

# Load documents using LangChain's DocumentLoaders
# This is from https://langchain.readthedocs.io/en/latest/modules/document_loaders/examples/csv.html

from langchain.document_loaders.csv_loader import CSVLoader
loader = CSVLoader(file_path='./example_data/mlb_teams_2012.csv')
data = loader.load()

jjsquady

Run this command in sail project folder:

docker-compose exec mysql bash

execute the mysql -u root -p command

provide the default password password

then executes

0xjac

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:

1. 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

xeoncross

Composer

the missing quick-start guide

We will assume we have a package/project called https://github.com/foo/bar

Most redistributable packages are hosted on a version control website such as Github or Bitbucket. Version control repositories often have a tagging system where we can define stable versions of our application. For example with git we can use the command:

git tag -a 1.0.0 -m 'First version.'

With this we have created version 1.0.0 of our application. This is a stable release which people can depend on. If we wanted to include "foo/bar" then we could create a composer.json and specify the tagged release we wanted: