estasney

## README.md

      
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                lurebat
                / README.md
            
            
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              November 1, 2024 07:36
            
              
                Jetmove - A script to enhance navigation and multiple carets in Jetbrains IDEs
              
          
    What is this?

Jetmove is a script I wrote to myself for some navigation and multiple carets features I felt were missing in Jetbrains IDEs.
It uses the excellent Live Plugin to run the script in the IDE.
All features support multiple carets, and are designed to work with them.
Features


## prefect_cleanup.py
import pendulum
import prefect
from dynaconf import settings
from prefect import schedules
from prefect.schedules import clocks

# Cron schedule to execute cleanup job. Currently set to run at 00:00 (UTC)
# every Sunday.
DATA_CLEANUP_SCHEDULE_CRON_STRING = "0 0 * * 0"

## recursion_flow.py
import prefect
from prefect import Flow, task, Task, case, Parameter
from prefect.environments import LocalEnvironment
from prefect.environments.storage import S3
from prefect.tasks.prefect import FlowRunTask
from prefect.tasks.control_flow import merge
from prefect.engine.results import PrefectResult


@task

## installing_nvidia_driver_cuda_cudnn_linux.md

      
              1 file
            
          
              50 forks
            
          
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                kmhofmann
                / installing_nvidia_driver_cuda_cudnn_linux.md
            
            
              Last active
              January 10, 2025 22:30
            
              
                Installing the NVIDIA driver, CUDA and cuDNN on Linux
              
          
    Installing the NVIDIA driver, CUDA and cuDNN on Linux (Ubuntu 20.04)

This is a companion piece to my instructions on building TensorFlow from source.
In particular, the aim is to install the following pieces of software

NVIDIA graphics card driver (v450.57)
CUDA (v11.0.2)
cuDNN (v8.0.2.39)

on an Ubuntu Linux system, in particular Ubuntu 20.04.

  
## tokenizations_post.md

      
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                tamuhey
                / tokenizations_post.md
            
            
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              July 27, 2024 14:46
            
              
                How to calculate the alignment between BERT and spaCy tokens effectively and robustly
              
          
    How to calculate the alignment between BERT and spaCy tokens effectively and robustly


site: https://tamuhey.github.io/tokenizations/
Natural Language Processing (NLP) has made great progress in recent years because of neural networks, which allows us to solve various tasks with end-to-end architecture. However, many NLP systems still require language-specific pre- and post-processing, especially in tokenizations. In this article, I describe an algorithm that simplifies calculating correspondence between tokens (e.g. BERT vs. spaCy), one such process. And I introduce Python and Rust libraries that implement this algorithm.
Here are the library and the demo site links:

repo: https://github.com/tamuhey/tokenizations


## home-server.md

      
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                nileshtrivedi
                / home-server.md
            
            
              Last active
              June 1, 2024 00:11
            
              
                Home Server setup: Raspberry PI on Internet via reverse SSH tunnel
              
          
    Raspberry Pi on Internet via reverse SSH tunnel

HackerNews discussed this with many alternative solutions: https://news.ycombinator.com/item?id=24893615
I already have my own domain name: mydomain.com. I wanted to be able to run some webapps on my Raspberry Pi 4B running
perpetually at home in headless mode (just needs 5W power and wireless internet). I wanted to be able to access these apps from public Internet. Dynamic DNS wasn't an option because my ISP blocks all incoming traffic. ngrok would work but the free plan is too restrictive.
I bought a cheap 2GB RAM, 20GB disk VM + a 25GB volume on Hetzner for about 4 EUR/month.
Hetzner gave me a static IP for it. I haven't purchased a floating IP yet.

  
## post_tags.py
from sqlalchemy import create_engine
from collections import namedtuple
import re
from tqdm.auto import tqdm

Tag = namedtuple('Tag', 'id name count regex')

USERNAME = ''
PASSWORD = ''
URL = 'localhost'

## index.html
<html>
</<!DOCTYPE html>
<html lang="en" dir="ltr">
  <head>
    <meta charset="utf-8">
    <title></title>
    <script src="https://d3js.org/d3.v5.js"></script>
    <script type="text/javascript" src="d3-hierarchy.js"></script>
    <style>
      .link {

## outlook_automation.py
import win32com.client as win32
from PIL import ImageGrab
from PIL import Image
import img2pdf
import subprocess
import traceback
import time


class MailDispatcher:

## draw_text_with_background_opencv.py
import cv2 # opencv
import numpy as np

font_scale = 1.5
font = cv2.FONT_HERSHEY_PLAIN

# set the rectangle background to white
rectangle_bgr = (255, 255, 255)
# make a black image
img = np.zeros((500, 500))
	import pendulum
	import prefect
	from dynaconf import settings
	from prefect import schedules
	from prefect.schedules import clocks

	# Cron schedule to execute cleanup job. Currently set to run at 00:00 (UTC)
	# every Sunday.
	DATA_CLEANUP_SCHEDULE_CRON_STRING = "0 0 * * 0"
	import prefect
	from prefect import Flow, task, Task, case, Parameter
	from prefect.environments import LocalEnvironment
	from prefect.environments.storage import S3
	from prefect.tasks.prefect import FlowRunTask
	from prefect.tasks.control_flow import merge
	from prefect.engine.results import PrefectResult


	@task
	from sqlalchemy import create_engine
	from collections import namedtuple
	import re
	from tqdm.auto import tqdm

	Tag = namedtuple('Tag', 'id name count regex')

	USERNAME = ''
	PASSWORD = ''
	URL = 'localhost'
	<html>
	</<!DOCTYPE html>
	<html lang="en" dir="ltr">
	<head>
	<meta charset="utf-8">
	<title></title>
	<script src="https://d3js.org/d3.v5.js"></script>
	<script type="text/javascript" src="d3-hierarchy.js"></script>
	<style>
	.link {
	import win32com.client as win32
	from PIL import ImageGrab
	from PIL import Image
	import img2pdf
	import subprocess
	import traceback
	import time


	class MailDispatcher:
	import cv2 # opencv
	import numpy as np

	font_scale = 1.5
	font = cv2.FONT_HERSHEY_PLAIN

	# set the rectangle background to white
	rectangle_bgr = (255, 255, 255)
	# make a black image
	img = np.zeros((500, 500))