skarlekar

"""
This Python script provides a utility to compute the cosine similarity between two text sentences using the TF-IDF 
(Term Frequency-Inverse Document Frequency) vectorization approach. 

Key Components:
1. Import Statements: The script begins by importing necessary modules:
   - TfidfVectorizer from sklearn.feature_extraction.text for converting text data into a matrix of TF-IDF features.
   - cosine_similarity from sklearn.metrics.pairwise to compute the similarity between two vectors in the TF-IDF space.
   - sys for accessing command-line arguments.

cedrickchee

4 Steps in Running LLaMA-7B on a M1 MacBook

The large language models usability

The problem with large language models is that you can’t run these locally on your laptop. Thanks to Georgi Gerganov and his llama.cpp project, it is now possible to run Meta’s LLaMA on a single computer without a dedicated GPU.

Running LLaMA

There are multiple steps involved in running LLaMA locally on a M1 Mac after downloading the model weights.

thomasaarholt

import numpy as np
from scipy import signal

def gaussian_kernel(n, std, normalised=False):
    '''
    Generates a n x n matrix with a centered gaussian 
    of standard deviation std centered on it. If normalised,
    its volume equals 1.'''
    gaussian1D = signal.gaussian(n, std)
    gaussian2D = np.outer(gaussian1D, gaussian1D)

tanaikech

Uploading Files From Local To Google Drive by Python without Quickstart

This is a sample script for uploading files from local PC to Google Drive using Python. In this sample, Quickstart is not used. So when you use this script, please retrieve access token.

Curl sample :

curl -X POST \
    -H "Authorization: Bearer ### access token ###" \
    -F "metadata={name : 'sample.png', parents: ['### folder ID ###']};type=application/json;charset=UTF-8" \
    -F "file=@sample.png;type=image/png" \
 "https://www.googleapis.com/upload/drive/v3/files?uploadType=multipart"

hiddentao

pragma solidity ^0.4.10;

contract RoleBasedAcl {
  address creator;
  mapping(address => mapping(string => bool)) roles;

  function RoleBasedAcl () {
    creator = msg.sender;
  }
  

maurelian

pragma solidity ^0.4.10;

// Update: Just use HardHat's: https://github.com/nomiclabs/hardhat/blob/master/packages/hardhat-core/console.sol

// Enables event logging of the format `console.log('descriptive string', variable)`, 
// without having to worry about the variable type (as long as an event has been declared for that type in the 
// Console contract.

contract Console {
    event LogUint(string, uint);

alexcasalboni

Amazon Rekognition - Python Code Samples

1. Labels Detection
2. Faces Detection
3. Faces Comparison
4. Faces Indexing
5. Faces Search

Mindgames

#!/bin/sh 
file=path/to/file 
bucket=your-bucket 
resource="/${bucket}/${file}" 
contentType="application/x-compressed-tar" 
dateValue="`date +'%a, %d %b %Y %H:%M:%S %z'`" 
stringToSign="GET 
${contentType} 
${dateValue} 
${resource}" 

wosephjeber

Installing ngrok on OSX

For Homebrew v2.6.x and below:

brew cask install ngrok

For Homebrew v2.7.x and above:

manjeshpv

// config/passport.js
				
// load all the things we need
var LocalStrategy   = require('passport-local').Strategy;

var mysql = require('mysql');

var connection = mysql.createConnection({
				  host     : 'localhost',
				  user     : 'root',