monk1337

{
    "Dataset": [
        "multimedqa",
        "medmcqa",
        "medqa_4options",
        "mmlu_anatomy",
        "mmlu_clinical_knowledge",
        "mmlu_college_biology",
        "mmlu_college_medicine",
        "mmlu_medical_genetics",

denguir

How to install CUDA & cuDNN on Ubuntu 22.04

Install NVIDIA drivers

Update & upgrade

sudo apt update && sudo apt upgrade

Remove previous NVIDIA installation

monk1337

#Use global flag
pip install gensim config --global http.sslVerify false


#on conda, disable the ssl
conda config --set ssl_verify False
conda update conda

# while downloading anything
import ssl

monk1337

cd /tmp
wget https://dl.google.com/go/go1.11.linux-amd64.tar.gz

sudo tar -xvf go1.11.linux-amd64.tar.gz
sudo mv go /usr/local
export GOROOT=/usr/local/go
export GOPATH=$HOME/go
export PATH=$GOPATH/bin:$GOROOT/bin:$PATH
source ~/.profile
go version

redknightlois

class Ralamb(Optimizer):

    def __init__(self, params, lr=1e-3, betas=(0.9, 0.999), eps=1e-8, weight_decay=0):
        defaults = dict(lr=lr, betas=betas, eps=eps, weight_decay=weight_decay)
        self.buffer = [[None, None, None] for ind in range(10)]
        super(Ralamb, self).__init__(params, defaults)

    def __setstate__(self, state):
        super(Ralamb, self).__setstate__(state)

eddex

How to install CUDA 10.1 on Ubuntu 18.04

A clean installation of Ubuntu 18.04.02 LTS was used.

This gist is an extension to the official docs, adding missing parts and instructions.

2 pre-install actions

follow the pre-installation actions on:

jphall663

iter_ = 0 
best_error = 0
best_iter = 0
best_model = None

col_sample_rates = [0.1, 0.5, 0.9]
subsamples = [0.1, 0.5, 0.9]
etas = [0.01, 0.001]
max_depths = [3, 6, 12, 15, 18]
reg_alphas = [0.01, 0.001]

Mahedi-61

#!/bin/bash

### steps ####
# Verify the system has a cuda-capable gpu
# Download and install the nvidia cuda toolkit and cudnn
# Setup environmental variables
# Verify the installation
###

### to verify your gpu is cuda enable check

W4ngatang

''' Script for downloading all GLUE data.

Note: for legal reasons, we are unable to host MRPC.
You can either use the version hosted by the SentEval team, which is already tokenized, 
or you can download the original data from (https://download.microsoft.com/download/D/4/6/D46FF87A-F6B9-4252-AA8B-3604ED519838/MSRParaphraseCorpus.msi) and extract the data from it manually.
For Windows users, you can run the .msi file. For Mac and Linux users, consider an external library such as 'cabextract' (see below for an example).
You should then rename and place specific files in a folder (see below for an example).

mkdir MRPC
cabextract MSRParaphraseCorpus.msi -d MRPC