jaymody

# If you're impatient like me, a progress bar can be a comforting way to impulsively check the progress
# of your docker save command
#
# You'll need tqdm installed (https://github.com/tqdm/tqdm) for this to work.

docker save IMAGE_NAME | tqdm --bytes --total $(docker image inspect IMAGE_NAME --format='{{.Size}}') > OUTPUT_TAR_NAME

jaymody

/* Making matrix multiplication 10x faster by making it cache-aware.

$ gcc -O3 main.c && ./a.out

Slow: 4.142s
Fast: 0.482s
*/

#include <stdio.h>
#include <stdlib.h>

jaymody

FROM tensorflow/tensorflow:1.13.2-py3

ENV DEBIAN_FRONTEND=noninteractive
RUN apt update -y && apt upgrade -y && apt install git -y

RUN git clone https://github.com/openai/gpt-2 /gpt-2
WORKDIR /gpt-2

RUN python3 -m pip install --upgrade pip && python3 -m pip install -r requirements.txt
RUN python3 download_model.py 124M

jaymody

# usage: curl -s https://gist.githubusercontent.com/jaymody/762417819fa017d75ff0870aa9ff0f2b/raw/setup.sh | sudo bash

# update and upgrade
apt update -y && apt upgrade -y

# packages
apt install -y \
    ack \
    coreutils \
    curl \

jaymody

jaymody

jaymody

jaymody

FROM nvcr.io/nvidia/pytorch:22.09-py3

ENV DEBIAN_FRONTEND=noninteractive

# "essential" packages
RUN apt update -y && apt upgrade -y && apt install -y \
    apt-transport-https \
    build-essential \
    ca-certificates \
    coreutils \

jaymody

import json
import os

import cohere
import numpy as np

names = ["Vet", "Police", "Engineer"]
descriptions = [
    "Vets are like doctors but for animals.",
    "Police protect and serve the community.",

jaymody

import jax
import jax.numpy as jnp


def forward_fn(params, X):
    for W, b in params[:-1]:
        X = jax.nn.relu(X @ W + b)

    final_W, final_b = params[-1]
    return X @ final_W + final_b