karpathy

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)

mra1385

benmarwick

# related to my question here: https://github.com/tidyverse/googledrive/issues/218

# How to get access to specific revisions of a google drive document? Yes, we can do that. 

# How to get the username for each revision, and the size of the document at each revision (bytes or words, assuming we are specifically talking about docs and not sheets or other types of files) Yes, we can do that.

# Goal is to measure the contributions of each author to a collaboratively-authored google doc with as little work as possible
# How to get access to specific revisions of a google drive document?

# Getting the revisions for a Google Doc

ezra-en

OUTDATED, PLEASE GO TO https://bteguide.rtfd.io FOR REFERENCE INSTEAD

Download and run this first:

• Minecraft Forge 1.12.2 - Latest

Run the .jar and Select Client Install and install. The directory should automatically be configured, so don't touch that.

Then download and put these into your /mods folder

DaMatrix

This guide assumes you already have a functional Minecraft Forge server with Cubic Chunks set up and running.

When editing configuration files, make sure to save the file before proceeding to the next step!

Before you begin: it is absolutely critical that you remove all client-side required mods from your server (aside from Cubic Chunks) so that a player with nothing other than Minecraft Forge and Cubic Chunks installed can join the server. If additional mods are required, vanilla players will not be able to connect!

Server Setup

1. Download the latest version of Cubic Chunks from Jenkins. You want CubicChunks-<version>-SNAPSHOT-all.jar.

shawwn

mp=1; size=7B; # to run 7B
mp=8; size=65B; # to run 65B
for seed in $(randint 1000000)
do
  export TARGET_FOLDER=~/ml/data/llama/LLaMA
  time python3 -m torch.distributed.run --nproc_per_node $mp example.py --ckpt_dir $TARGET_FOLDER/$size --tokenizer_path $TARGET_FOLDER/tokenizer.model --seed $seed --max_seq_len 2048 --max_gen_len 2048 --count 0 | tee -a ${size}_startrek.txt 
done

sshh12

You are a powerful agentic AI coding assistant, powered by Claude 3.5 Sonnet. You operate exclusively in Cursor, the world's best IDE.

You are pair programming with a USER to solve their coding task.
The task may require creating a new codebase, modifying or debugging an existing codebase, or simply answering a question.
Each time the USER sends a message, we may automatically attach some information about their current state, such as what files they have open, where their cursor is, recently viewed files, edit history in their session so far, linter errors, and more.
This information may or may not be relevant to the coding task, it is up for you to decide.
Your main goal is to follow the USER's instructions at each message, denoted by the <user_query> tag.

<communication>
1. Be conversational but professional.