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iTerm2 Ollama Integration

A guide on using Ollama as the OpenAI API provider for inline completions in iTerm2.

Configuration

• API URL: http://127.0.0.1:11434/v1/completions
• Model: mistral
• Tokens: 4000
• Use legacy completions API: true

cshen

Password-store keeps your passwords (or any other sensitive information) saved in GnuPG encrypted files organized in ~/.password-store. For more information about GPG, consult the GNU Privacy Handbook.

Getting started

To get started, install pass and generate a keypair.

$ brew install pass
$ gpg --gen-key
$ gpg --list-keys

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<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
	<key>AllowClipboardAccess</key>
	<true/>
	<key>AppleAntiAliasingThreshold</key>
	<integer>1</integer>
	<key>ApplePressAndHoldEnabled</key>

cshen

Running emscripten on OS X

There are a number of additional dependencies required for getting things installed on OS X. Starting with a blank slate OS X machine, this is the process it takes:

# Install Xcode Command Line Tools

# Install Homebrew
ruby -e "$(curl -fsSkL raw.github.com/mxcl/homebrew/go)"

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% Title % Name % Date

My first slide

List

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Installing CUDA Toolkit 5.5 on Ubuntu 12.10 Linux


The following explains how to install CUDA Toolkit 5.5 on 64-bit Ubuntu 12.10 Linux. I have tested it on a self-assembled desktop with AMD Phenom II X4 CPU, 4GB RAM, 500GB hard drive, 650W power supply, and NVIDIA GeForce GTX 550 Ti graphics card. The instruction assumes you have the necessary CUDA compatible hardware support. Depending on your system configuration, your mileage may vary.
CUDA Repository
Retrieve the CUDA repository package for Ubuntu 12.10 from the CUDA download site and install it in a terminal.
 $ sudo dpkg -i cuda-repo-ubuntu1210_5.5-0_amd64.deb
 $ sudo apt-get update
Linux Kernel Header
Then you need to install the necessary Linux kernel headers.

cshen

Install Pylearn2 on a Ubuntu box
https://github.com/lisa-lab/pylearn2


Assume that the default version of Python is 2.7.3

Tested on a machine with
- Linux 3.2.0-26-generic x86_64 GNU/Linux
- Ubuntu 12.04.2 LTS (Precise Pangolin)

cshen

Installing CUDA 5 on Ubuntu 12.04

copied from: http://sn0v.wordpress.com/2012/12/07/installing-cuda-5-on-ubuntu-12-04/

This is a follow up to my previous post which was aimed at CUDA 4.2 on Ubuntu 12.04. Although 12.10 is out, it’s not as stable as I would like it to be – I’d recommend sticking with Ubuntu 12.04 for development unless you have specific reasons to upgrade. With CUDA 5, Nvidia has greatly simplified the installation process for Linux, packaging the CUDA toolkit, the SDK and the development drivers all in a neat little package.


A few points before we begin though -

As always, a working CUDA installation requires a CUDA capable card.

cshen

# remgit.sh
# Creates a remote git repository from the current local directory

# Configuration
# Replace SSH_USERNAME, SSH_HOST, SSH_GIT_PATH with your details
USER=SSH_USERNAME
HOST=SSH_HOST
GIT_PATH=SSH_GIT_PATH

REPO=${PWD##*/}

cshen

/**

The following example uses this function to calculate the matrix-vector product using 
a blas/lapack routine:

  / 3 1 3 \   / -1 \ 
  | 1 5 9 | * | -1 |. 
  \ 2 6 5 /   \  1 / 

D2 version based on the C version at http://www.seehuhn.de/pages/linear