padeoe

How to upgrade the Linux Kernel of debian 8 jessie

Debian 8 のカーネルをアップグレードする方法です。

Environment

Microsoft Windows Server 2012 R2
Hyper-V
Debian 8.2 jessie

git commit stats

Commands to get commit statistics for a Git repository from the command line -
using git log, git shortlog and friends.

🤗Huggingface Model Downloader

Note

(2025-01-08) Add feature for 🏷️Tag(Revision) Selection, contributed by @Bamboo-D.
(2024-12-17) Add feature for ⚡Quick Startup and ⏭️Fast Resume, enabling skipping of downloaded files, while removing the git clone dependency to accelerate file list retrieval.

Considering the lack of multi-threaded download support in the official huggingface-cli, and the inadequate error handling in hf_transfer, This command-line tool leverages curl and aria2c for fast and robust downloading of models and datasets.

Features

⏯️ Resume from breakpoint: You can re-run it or Ctrl+C anytime.

	import ConfigParser, mmap

	config_file = "/usr/share/applications/google-chrome.desktop"
	add_string_to_each_section = ["StartupWMClass", "Google-chrome-stable"]
	option = add_string_to_each_section[0]
	value = add_string_to_each_section[1]


	class Fixer:
	def check(self, cf, option, value):

	if (!String.prototype.repeat) {
	// polyfill from https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/String/repeat
	String.prototype.repeat = function(count) {
	'use strict';
	if (this == null) {
	throw new TypeError('can\'t convert ' + this + ' to object');
	}
	var str = '' + this;
	count = +count;
	if (count != count) {

	#put the these lines before importing any module from keras.
	import tensorflow as tf

	from keras.backend.tensorflow_backend import set_session
	config = tf.ConfigProto()
	config.gpu_options.allow_growth = True
	config.gpu_options.visible_device_list = "0" #only the gpu 0 is allowed
	set_session(tf.Session(config=config))

	import numpy as np
	import pandas as pd
	from keras.callbacks import Callback

	class ScoreMetric(Callback):
	def __init__(self, score_func, num_input=1, num_target=1):
	super(ScoreMetric, self).__init__()
	self.num_input = num_input
	self.num_target = num_target
	self.score_func = score_func