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1636769189
In this article, we’ll discuss information about the ZillaMatrix project and ZMAX token. What is ZillaMatrix (ZMAX) | What is ZMAX token?
ZillaMatrix (ZMAX) has been called one of the most interesting economic experiments in the DeFi space for several reasons. It’s rebase token with focus on the gaming and NFT space. The elastic supply smart contract that works in a way whereby the circulating supply expands or contracts due to changes in token price. … Rebase is essentially an increase or decrease in the total supply of a token across including all holders. According to the white paper, ZMAX taxes every transation a total fee of 10% and rewards it’s holders in $FLOKIN one of the leading multi-chain NFT Marketplace tokens.
Lastly, ZMAX is well-known for its strong developer team, marketing and meme game, allowing it to build and grow one of the most vibrant communities in the space!
ZillaMatrix (ZMAX)
A rebase token, born to be unleashed and destined to reign in the ZillaMatrix.
An elastic supply, or rebase token, works in a way that allows the circulating supply to expand or contract in response to changes in token price. This increases or decreases in supply function via a mechanism called re-basing. When a rebase occurs, the supply of the token is increased or decreased algorithmically, based on the current price of each token. In some ways, elastic supply tokens can be paralleled with stable coins in the sense that both aim to achieve a target price. The key difference in rebasing is that tokens aim to achieve it via an elastic supply.
For instance, say we have an elastic supply token that aims to achieve a value of 1 USD. If the price is above 1 USD, the re-base increases the current supply and will adjust accordingly by reducing the value of each token. Conversely, if the price is below 1 USD, the re-base will decrease the supply and the price of each token will reflect an increase in price.
Tokenomics
From its qualities to its distribution and much more about ZillaMatrix… Reflection rewards are in flokinomics (FLOKIN)
How and Where to Buy ZMAX token?
ZMAX token is now live on the Binance mainnet. The token address for ZMAX is 0xd05a0c5c68acba9aa9952fa65189038840752977. Be cautious not to purchase any other token with a smart contract different from this one (as this can be easily faked). We strongly advise to be vigilant and stay safe throughout the launch. Don’t let the excitement get the best of you.
Just be sure you have enough BNB in your wallet to cover the transaction fees.
Join To Get BNB (Binance Coin)! ☞ CLICK HERE
You will have to first buy one of the major cryptocurrencies, usually either Bitcoin (BTC), Ethereum (ETH), Tether (USDT), Binance (BNB)…
We will use Binance Exchange here as it is one of the largest crypto exchanges that accept fiat deposits.
Once you finished the KYC process. You will be asked to add a payment method. Here you can either choose to provide a credit/debit card or use a bank transfer, and buy one of the major cryptocurrencies, usually either Bitcoin (BTC), Ethereum (ETH), Tether (USDT), Binance (BNB)…
Step by Step Guide : What is Binance | How to Create an account on Binance (Updated 2021)
Next step
You need a wallet address to Connect to Pancakeswap Decentralized Exchange, we use Metamask wallet
If you don’t have a Metamask wallet, read this article and follow the steps ☞ What is Metamask wallet | How to Create a wallet and Use
Transfer $BNB to your new Metamask wallet from Binance wallet
Next step
Connect Metamask Wallet to Pancakeswap Decentralized Exchange and Buy, Swap ZMAX token
Contract: 0xd05a0c5c68acba9aa9952fa65189038840752977
Read more: What is Pancakeswap | Beginner’s Guide on How to Use Pancakeswap
The top exchange for trading in ZMAX token is currently: PancakeSwap (V2)
Top exchanges for token-coin trading. Follow instructions and make unlimited money
☞ Binance ☞ Bittrex ☞ Poloniex ☞ Bitfinex ☞ Huobi ☞ MXC ☞ ProBIT ☞ Gate.io ☞ Coinbase
🔺DISCLAIMER: The Information in the post isn’t financial advice, is intended FOR GENERAL INFORMATION PURPOSES ONLY. Trading Cryptocurrency is VERY risky. Make sure you understand these risks and that you are responsible for what you do with your money.
🔥 If you’re a beginner. I believe the article below will be useful to you ☞ What You Should Know Before Investing in Cryptocurrency – For Beginner
⭐ ⭐ ⭐The project is of interest to the community ☞ **—–https://geekcash.org—–**⭐ ⭐ ⭐
Find more information ZMAX token ☞ Website
I hope this post will help you. Don’t forget to leave a like, comment and sharing it with others. Thank you!
1658068560
WordsCounted
We are all in the gutter, but some of us are looking at the stars.
— Oscar Wilde
WordsCounted is a Ruby NLP (natural language processor). WordsCounted lets you implement powerful tokensation strategies with a very flexible tokeniser class.
["Bayrūt"]and not["Bayr", "ū", "t"], for example.
Add this line to your application’s Gemfile:
gem 'words_counted'
And then execute:
$ bundle
Or install it yourself as:
$ gem install words_counted
Pass in a string or a file path, and an optional filter and/or regexp.
counter = WordsCounted.count( "We are all in the gutter, but some of us are looking at the stars." ) # Using a file counter = WordsCounted.from_file("path/or/url/to/my/file.txt")
.count and .from_file are convenience methods that take an input, tokenise it, and return an instance of WordsCounted::Counter initialized with the tokens. The WordsCounted::Tokeniser and WordsCounted::Counter classes can be used alone, however.
WordsCounted.count(input, options = {})
Tokenises input and initializes a WordsCounted::Counter object with the resulting tokens.
counter = WordsCounted.count("Hello Beirut!")
Accepts two options: exclude and regexp. See Excluding tokens from the analyser and Passing in a custom regexp respectively.
WordsCounted.from_file(path, options = {})
Reads and tokenises a file, and initializes a WordsCounted::Counter object with the resulting tokens.
counter = WordsCounted.from_file("hello_beirut.txt")
Accepts the same options as .count.
The tokeniser allows you to tokenise text in a variety of ways. You can pass in your own rules for tokenisation, and apply a powerful filter with any combination of rules as long as they can boil down into a lambda.
Out of the box the tokeniser includes only alpha chars. Hyphenated tokens and tokens with apostrophes are considered a single token.
#tokenise([pattern: TOKEN_REGEXP, exclude: nil])
tokeniser = WordsCounted::Tokeniser.new("Hello Beirut!").tokenise # With `exclude` tokeniser = WordsCounted::Tokeniser.new("Hello Beirut!").tokenise(exclude: "hello") # With `pattern` tokeniser = WordsCounted::Tokeniser.new("I <3 Beirut!").tokenise(pattern: /[a-z]/i)
See Excluding tokens from the analyser and Passing in a custom regexp for more information.
The WordsCounted::Counter class allows you to collect various statistics from an array of tokens.
#token_count
Returns the token count of a given string.
counter.token_count #=> 15
#token_frequency
Returns a sorted (unstable) two-dimensional array where each element is a token and its frequency. The array is sorted by frequency in descending order.
counter.token_frequency [ ["the", 2], ["are", 2], ["we", 1], # ... ["all", 1] ]
#most_frequent_tokens
Returns a hash where each key-value pair is a token and its frequency.
counter.most_frequent_tokens { "are" => 2, "the" => 2 }
#token_lengths
Returns a sorted (unstable) two-dimentional array where each element contains a token and its length. The array is sorted by length in descending order.
counter.token_lengths [ ["looking", 7], ["gutter", 6], ["stars", 5], # ... ["in", 2] ]
#longest_tokens
Returns a hash where each key-value pair is a token and its length.
counter.longest_tokens { "looking" => 7 }
#token_density([ precision: 2 ])
Returns a sorted (unstable) two-dimentional array where each element contains a token and its density as a float, rounded to a precision of two. The array is sorted by density in descending order. It accepts a precision argument, which must be a float.
counter.token_density [ ["are", 0.13], ["the", 0.13], ["but", 0.07 ], # ... ["we", 0.07 ] ]
#char_count
Returns the char count of tokens.
counter.char_count #=> 76
#average_chars_per_token([ precision: 2 ])
Returns the average char count per token rounded to two decimal places. Accepts a precision argument which defaults to two. Precision must be a float.
counter.average_chars_per_token #=> 4
#uniq_token_count
Returns the number of unique tokens.
counter.uniq_token_count #=> 13
You can exclude anything you want from the input by passing the exclude option. The exclude option accepts a variety of filters and is extremely flexible.
:odd?.
tokeniser = WordsCounted::Tokeniser.new( "Magnificent! That was magnificent, Trevor." ) # Using a string tokeniser.tokenise(exclude: "was magnificent") # => ["that", "trevor"] # Using a regular expression tokeniser.tokenise(exclude: /trevor/) # => ["magnificent", "that", "was", "magnificent"] # Using a lambda tokeniser.tokenise(exclude: ->(t) { t.length < 4 }) # => ["magnificent", "that", "magnificent", "trevor"] # Using symbol tokeniser = WordsCounted::Tokeniser.new("Hello! محمد") tokeniser.tokenise(exclude: :ascii_only?) # => ["محمد"] # Using an array tokeniser = WordsCounted::Tokeniser.new( "Hello! اسماءنا هي محمد، كارولينا، سامي، وداني" ) tokeniser.tokenise( exclude: [:ascii_only?, /محمد/, ->(t) { t.length > 6}, "و"] ) # => ["هي", "سامي", "وداني"]
The default regexp accounts for letters, hyphenated tokens, and apostrophes. This means twenty-one is treated as one token. So is Mohamad’s.
/[p{Alpha}-']+/
You can pass your own criteria as a Ruby regular expression to split your string as desired.
For example, if you wanted to include numbers, you can override the regular expression:
counter = WordsCounted.count("Numbers 1, 2, and 3", pattern: /[p{Alnum}-']+/) counter.tokens #=> ["numbers", "1", "2", "and", "3"]
Use the from_file method to open files. from_file accepts the same options as .count. The file path can be a URL.
counter = WordsCounted.from_file("url/or/path/to/file.text")
A hyphen used in leu of an em or en dash will form part of the token. This affects the tokeniser algorithm.
counter = WordsCounted.count("How do you do?-you are well, I see.") counter.token_frequency [ ["do", 2], ["how", 1], ["you", 1], ["-you", 1], # WTF, mate! ["are", 1], # ... ]
In this example -you and you are separate tokens. Also, the tokeniser does not include numbers by default. Remember that you can pass your own regular expression if the default behaviour does not fit your needs.
The program will normalise (downcase) all incoming strings for consistency and filters.
def self.from_url # open url and send string here after removing html end
Are you using WordsCounted to do something interesting? Please tell me about it.
Visit this website for one example of what you can do with WordsCounted.
Contributors
See contributors.
git checkout -b my-new-feature)git commit -am 'Add some feature')git push origin my-new-feature)
Author: Abitdodgy
Source Code: https://github.com/abitdodgy/words_counted
License: MIT license
1659601560
We are all in the gutter, but some of us are looking at the stars.
— Oscar Wilde
WordsCounted is a Ruby NLP (natural language processor). WordsCounted lets you implement powerful tokensation strategies with a very flexible tokeniser class.
Are you using WordsCounted to do something interesting? Please tell me about it.
Visit this website for one example of what you can do with WordsCounted.
["Bayrūt"]and not["Bayr", "ū", "t"], for example.
Add this line to your application’s Gemfile:
gem 'words_counted'
And then execute:
$ bundle
Or install it yourself as:
$ gem install words_counted
Pass in a string or a file path, and an optional filter and/or regexp.
counter = WordsCounted.count( "We are all in the gutter, but some of us are looking at the stars." ) # Using a file counter = WordsCounted.from_file("path/or/url/to/my/file.txt")
.count and .from_file are convenience methods that take an input, tokenise it, and return an instance of WordsCounted::Counter initialized with the tokens. The WordsCounted::Tokeniser and WordsCounted::Counter classes can be used alone, however.
WordsCounted.count(input, options = {})
Tokenises input and initializes a WordsCounted::Counter object with the resulting tokens.
counter = WordsCounted.count("Hello Beirut!")
Accepts two options: exclude and regexp. See Excluding tokens from the analyser and Passing in a custom regexp respectively.
WordsCounted.from_file(path, options = {})
Reads and tokenises a file, and initializes a WordsCounted::Counter object with the resulting tokens.
counter = WordsCounted.from_file("hello_beirut.txt")
Accepts the same options as .count.
The tokeniser allows you to tokenise text in a variety of ways. You can pass in your own rules for tokenisation, and apply a powerful filter with any combination of rules as long as they can boil down into a lambda.
Out of the box the tokeniser includes only alpha chars. Hyphenated tokens and tokens with apostrophes are considered a single token.
#tokenise([pattern: TOKEN_REGEXP, exclude: nil])
tokeniser = WordsCounted::Tokeniser.new("Hello Beirut!").tokenise # With `exclude` tokeniser = WordsCounted::Tokeniser.new("Hello Beirut!").tokenise(exclude: "hello") # With `pattern` tokeniser = WordsCounted::Tokeniser.new("I <3 Beirut!").tokenise(pattern: /[a-z]/i)
See Excluding tokens from the analyser and Passing in a custom regexp for more information.
The WordsCounted::Counter class allows you to collect various statistics from an array of tokens.
#token_count
Returns the token count of a given string.
counter.token_count #=> 15
#token_frequency
Returns a sorted (unstable) two-dimensional array where each element is a token and its frequency. The array is sorted by frequency in descending order.
counter.token_frequency [ ["the", 2], ["are", 2], ["we", 1], # ... ["all", 1] ]
#most_frequent_tokens
Returns a hash where each key-value pair is a token and its frequency.
counter.most_frequent_tokens { "are" => 2, "the" => 2 }
#token_lengths
Returns a sorted (unstable) two-dimentional array where each element contains a token and its length. The array is sorted by length in descending order.
counter.token_lengths [ ["looking", 7], ["gutter", 6], ["stars", 5], # ... ["in", 2] ]
#longest_tokens
Returns a hash where each key-value pair is a token and its length.
counter.longest_tokens { "looking" => 7 }
#token_density([ precision: 2 ])
Returns a sorted (unstable) two-dimentional array where each element contains a token and its density as a float, rounded to a precision of two. The array is sorted by density in descending order. It accepts a precision argument, which must be a float.
counter.token_density [ ["are", 0.13], ["the", 0.13], ["but", 0.07 ], # ... ["we", 0.07 ] ]
#char_count
Returns the char count of tokens.
counter.char_count #=> 76
#average_chars_per_token([ precision: 2 ])
Returns the average char count per token rounded to two decimal places. Accepts a precision argument which defaults to two. Precision must be a float.
counter.average_chars_per_token #=> 4
#uniq_token_count
Returns the number of unique tokens.
counter.uniq_token_count #=> 13
You can exclude anything you want from the input by passing the exclude option. The exclude option accepts a variety of filters and is extremely flexible.
:odd?.
tokeniser = WordsCounted::Tokeniser.new( "Magnificent! That was magnificent, Trevor." ) # Using a string tokeniser.tokenise(exclude: "was magnificent") # => ["that", "trevor"] # Using a regular expression tokeniser.tokenise(exclude: /trevor/) # => ["magnificent", "that", "was", "magnificent"] # Using a lambda tokeniser.tokenise(exclude: ->(t) { t.length < 4 }) # => ["magnificent", "that", "magnificent", "trevor"] # Using symbol tokeniser = WordsCounted::Tokeniser.new("Hello! محمد") tokeniser.tokenise(exclude: :ascii_only?) # => ["محمد"] # Using an array tokeniser = WordsCounted::Tokeniser.new( "Hello! اسماءنا هي محمد، كارولينا، سامي، وداني" ) tokeniser.tokenise( exclude: [:ascii_only?, /محمد/, ->(t) { t.length > 6}, "و"] ) # => ["هي", "سامي", "وداني"]
The default regexp accounts for letters, hyphenated tokens, and apostrophes. This means twenty-one is treated as one token. So is Mohamad’s.
/[p{Alpha}-']+/
You can pass your own criteria as a Ruby regular expression to split your string as desired.
For example, if you wanted to include numbers, you can override the regular expression:
counter = WordsCounted.count("Numbers 1, 2, and 3", pattern: /[p{Alnum}-']+/) counter.tokens #=> ["numbers", "1", "2", "and", "3"]
Use the from_file method to open files. from_file accepts the same options as .count. The file path can be a URL.
counter = WordsCounted.from_file("url/or/path/to/file.text")
A hyphen used in leu of an em or en dash will form part of the token. This affects the tokeniser algorithm.
counter = WordsCounted.count("How do you do?-you are well, I see.") counter.token_frequency [ ["do", 2], ["how", 1], ["you", 1], ["-you", 1], # WTF, mate! ["are", 1], # ... ]
In this example -you and you are separate tokens. Also, the tokeniser does not include numbers by default. Remember that you can pass your own regular expression if the default behaviour does not fit your needs.
The program will normalise (downcase) all incoming strings for consistency and filters.
def self.from_url # open url and send string here after removing html end
See contributors.
git checkout -b my-new-feature)git commit -am 'Add some feature')git push origin my-new-feature)
Author: abitdodgy
Source code: https://github.com/abitdodgy/words_counted
License: MIT license
#ruby #ruby-on-rails
1622197808
SafeMoon is a decentralized finance (DeFi) token. This token consists of RFI tokenomics and auto-liquidity generating protocol. A DeFi token like SafeMoon has reached the mainstream standards under the Binance Smart Chain. Its success and popularity have been immense, thus, making the majority of the business firms adopt this style of cryptocurrency as an alternative.
A DeFi token like SafeMoon is almost similar to the other crypto-token, but the only difference being that it charges a 10% transaction fee from the users who sell their tokens, in which 5% of the fee is distributed to the remaining SafeMoon owners. This feature rewards the owners for holding onto their tokens.
Read More @ https://bit.ly/3oFbJoJ
#create a defi token like safemoon #defi token like safemoon #safemoon token #safemoon token clone #defi token
1621844791
The SafeMoon Token Clone Development is the new trendsetter in the digital world that brought significant changes to benefit the growth of investors’ business in a short period. The SafeMoon token clone is the most widely discussed topic among global users for its value soaring high in the marketplace. The SafeMoon token development is a combination of RFI tokenomics and the auto-liquidity generating process. The SafeMoon token is a replica of decentralized finance (DeFi) tokens that are highly scalable and implemented with tamper-proof security.
The SafeMoon tokens execute efficient functionalities like RFI Static Rewards, Automated Liquidity Provisions, and Automatic Token Burns. The SafeMoon token is considered the most advanced stable coin in the crypto market. It gained global audience attention for managing the stability of asset value without any fluctuations in the marketplace. The SafeMoon token clone is completely decentralized that eliminates the need for intermediaries and benefits the users with less transaction fee and wait time to overtake the traditional banking process.
The SafeMoon Token Clone Development is a promising future for upcoming investors and startups to increase their business revenue in less time. The SafeMoon token clone has great demand in the real world among millions of users for its value in the market. Investors can contact leading Infinite Block Tech to gain proper assistance in developing a world-class SafeMoon token clone that increases the business growth in less time.
#safemoon token #safemoon token clone #safemoon token clone development #defi token
1624230000
How to Buy FEG Token – The EASIEST Method 2021
In today’s video, I will be showing you guys how to buy the FEG token/coin using Trust Wallet and Pancakeswap. This will work for both iOS and Android devices!
📺 The video in this post was made by More LimSanity
The origin of the article: https://www.youtube.com/watch?v=LAVwpiEN6bg
🔺 DISCLAIMER: The article is for information sharing. The content of this video is solely the opinions of the speaker who is not a licensed financial advisor or registered investment advisor. Not investment advice or legal advice.
Cryptocurrency trading is VERY risky. Make sure you understand these risks and that you are responsible for what you do with your money
🔥 If you’re a beginner. I believe the article below will be useful to you ☞ What You Should Know Before Investing in Cryptocurrency – For Beginner
⭐ ⭐ ⭐The project is of interest to the community. Join to Get free ‘GEEK coin’ (GEEKCASH coin)!
☞ **—–CLICK HERE—–**⭐ ⭐ ⭐
Thanks for visiting and watching! Please don’t forget to leave a like, comment and share!
#bitcoin #blockchain #feg token #token #how to buy feg token #how to buy feg token – the easiest method 2021
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