What is Shibaverse (VERSE) | What is VERSE token

In this article, we'll discuss information about the Shibaverse project and VERSE token.

ShibaVerse is a Metaverse aiming to be a decentralized, digital world on blockchain, bringing features such as virtual reality, digital real estate, NFTs, Play2Earn (GameFi), freelance jobs, and interactive aspects all into one sleek and captivating environment.

Shiba Academy, community online events and meetups, virtual 3D galleries with art created by users, property/pet/accessories NFT marketplace, gaming challenges – that is what will take place in Shibaverse and as our virtual world will be open to community ideas. We sincerely believe it is only the beginning.

VERSE is the native utility ERC20 token that is used for: - purchasing new real estates and other nft assets - participating in pay2earn features

Features

NFT 2.0 marketplace

Play2earn gaming

VR experience and virtual walks

Verse token market buyback and burn

Virtual shops

Freelance job opportunities

Defi tools utilizing Shiba ecosystem

Interactive educational tracks

Goals of Shibaverse

Support and promote Shiba Token Ecosystem: We want our platform to be a beginner-friendly metaverse reflection of the Shiba ecosystem. By districts names corresponding to Shiba Token platforms, social events and games for Shiba community or benefits for projects accepted by Shibaccelerator. We belive we can onboard much new interest and many new users to Shiba products.

Entertain and bring financial opportunities for Shiba community: We want to bring the community as many financial incentives as we can – whether by Verse token price appreciation, Shibaswap users airdrop, play2earn gaming, NFT marketplace or freelance work opportunities regarding Shibaverse development.

Educate young generation: Blockchain gives new chances for those who would have never gotten them any other way. We see children playing Axie and financially supporting their parents in poorer parts of the world. We want to increase those chances by educating younger generations in a fun and interactive way. Shiba Academy and Shiba Studio will be places where teenagers and even children can find guidance on how to be secure and make the most of the blockchain world. We love young people!

Your Shiba NFT 2.0

• Open door to Shibaverse: Having your Shiba Inu NFT will enable you to participate in different Shibaverse features. Among others you can participate in community events, game challenges, taking payable jobs regarding development of our metaverse. Also, if you are a parent you can take part with your child in Shiba Academy educational track.
• Uniqueness of your Shiba: Each Shiba Inu will be unique. It will have its own combination of appearance, skills, strengths and weaknesses. It will grow, with your engagement learn new skills and need your care.
• Having puppies: You can own many Shibas and if you own a male and female they can reproduce NFT Shiba puppies. They will inherit their parents characteristics randomly and as time will pass they also may have offspring. The differences will make some puppies more valuable at market than others, as some may be more efficient in play2earn competitions.

Your real-estate

• Buy, sell, lend: Each piece of land, apartment or house will be a blockchain NFT and as a result of that can be sold, bought or lent in a secure and trustless way. Depending on district, location, size it will have its own market value which as we believe will increase as popularity of platform grows.
• Have your own puppies and earn: Owning a property will enable your Shibas to have offspring that can bring you financial opportunities (as after first generation of shibas, new shibas in our metaverse can come in majority only from birth from parents).
  The greater size of your property the more shiba’s couples you can place and the more offspring you may have.
• 3D virtual NFT shops and galleries: As a full-fledged habitant of our metaverse you will be able to place your art in our marketplace. In further stages of metaverse development your space can be uniquely designed and 3D rendered in a VR way. You can place your NFT’s art there and invite potential buyers to visit. This feature may take time for us to build.

Accessories

• Upgrade appearance or boost skills: Your Shiba may have unique wearing’s and accessories that may change appearance and even boost some skills in our games.
• Create and sell: As they will be NFT’s all can be traded in our marketplace. You will be able to create your own custom wearing’s and offer them to other users. It can be another great opportunity to earn.
• Discover, learn and earn, collect: You will be able to collect accessories during discovering our world or taking lessons in Shiba Academy,

Play2earn

• A living creature: Your shiba will not be only an image. As a living creature, it can take part in games and competitions. And as we all believe in Shiba community creativity, we hope you will help us with writing exciting scenarios.
• Unique in-game skills: As all Shibas will have their individual strengths and weaknesses some may perform better than others in certain tasks. They also may cooperate in teams.
• Earn: If your shiba wins you will be rewarded too as Verse will be at stake. But no pet will be harmed during a game 🙂

VERSE Token

VERSE token is a utility ERC-20 token across Shibaverse. Verse will be necessary for purchasing real-estate, land, special editions of Shibas, and renting commercial space. It will be used for paying in the community for freelance jobs. It will also play a role in play2earn mechanisms.

Each time a new user wants to buy newly built real estate, they will have to buy VERSE token from market to pay for the NFT property. Those tokens will not come back to market in the same way. Some tokens will be divided among stakers, some will go to project development fund, some will be donated for children’s charity and some will be burnt forever decreasing circulating supply.

Token Distribution

We want Shibaverse to be a community based project and for that reason 100% of circulating supply goes to community . No VC's and seed investors dumping the price!

DEX liquidity80%

Shibaswap users airdrop20%

Token Details

 

Token Ticker	VERSE
Total supply:	1 000 000 000
Initial circulating supply	800 000 000
Other supply	200 000 000 (reserved for Shiba ecosytem users)

How and Where to Buy VERSE token?

VERSE has been listed on a number of crypto exchanges, unlike other main cryptocurrencies, it cannot be directly purchased with fiats money. However, You can still easily buy this coin by first buying Bitcoin, ETH, USDT, BNB from any large exchanges and then transfer to the exchange that offers to trade this coin, in this guide article we will walk you through in detail the steps to buy VERSE token.

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.

Binance is a popular cryptocurrency exchange which was started in China but then moved their headquarters to the crypto-friendly Island of Malta in the EU. Binance is popular for its crypto to crypto exchange services. Binance exploded onto the scene in the mania of 2017 and has since gone on to become the top crypto exchange in the world.

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)…

☞ SIGN UP ON BINANCE

Step by Step Guide : What is Binance | How to Create an account on Binance (Updated 2021)

Next step - Transfer your cryptos to an Altcoin Exchange

Since VERSE is an altcoin we need to transfer our coins to an exchange that VERSE can be traded. Below is a list of exchanges that offers to trade VERSE in various market pairs, head to their websites and register for an account.

Once finished you will then need to make a BTC/ETH/USDT/BNB deposit to the exchange from Binance depending on the available market pairs. After the deposit is confirmed you may then purchase VERSE from the exchange.

The top exchange for trading in VERSE token is currently:  Sushiswap, and 0x Protocol.

ETH Contract: 0x7ae0d42f23c33338de15bfa89c7405c068d9dc0a

Find more information VERSE token

☞ Website ☞ Explorer ☞ Social Channel ☞ Social Channel 2 ☞ Social Channel 3 ☞ Coinmarketcap

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. Join to Get free ‘GEEK coin’ (GEEKCASH coin)!

☞ **-----https://geekcash.org-----**⭐ ⭐ ⭐

I hope this post will help you. Don't forget to leave a like, comment and sharing it with others. Thank you!

#bitcoin #cryptocurrency

What is GEEK

Buddha Community

Words Counted: A Ruby Natural Language Processor.

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.

Are you using WordsCounted to do something interesting? Please tell me about it.

 

Demo

Visit this website for one example of what you can do with WordsCounted.

Features

• Out of the box, get the following data from any string or readable file, or URL:
  • Token count and unique token count
  • Token densities, frequencies, and lengths
  • Char count and average chars per token
  • The longest tokens and their lengths
  • The most frequent tokens and their frequencies.
• A flexible way to exclude tokens from the tokeniser. You can pass a string, regexp, symbol, lambda, or an array of any combination of those types for powerful tokenisation strategies.
• Pass your own regexp rules to the tokeniser if you prefer. The default regexp filters special characters but keeps hyphens and apostrophes. It also plays nicely with diacritics (UTF and unicode characters): Bayrūt is treated as ["Bayrūt"] and not ["Bayr", "ū", "t"], for example.
• Opens and reads files. Pass in a file path or a url instead of a string.

Installation

Add this line to your application's Gemfile:

gem 'words_counted'

And then execute:

$ bundle

Or install it yourself as:

$ gem install words_counted

Usage

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.

API

WordsCounted

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.

Tokeniser

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.

Counter

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

Excluding tokens from the tokeniser

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.

1. A space-delimited string. The filter will normalise the string.
2. A regular expression.
3. A lambda.
4. A symbol that names a predicate method. For example :odd?.
5. An array of any combination of the above.

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"]

Passing in a custom regexp

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"]

Opening and reading files

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")

Gotchas

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.

A note on case sensitivity

The program will normalise (downcase) all incoming strings for consistency and filters.

Roadmap

Ability to open URLs

def self.from_url
  # open url and send string here after removing html
end

Contributors

See contributors.

Contributing

1. Fork it
2. Create your feature branch (git checkout -b my-new-feature)
3. Commit your changes (git commit -am 'Add some feature')
4. Push to the branch (git push origin my-new-feature)
5. Create new Pull Request

---

Author: abitdodgy
Source code: https://github.com/abitdodgy/words_counted
License: MIT license

#ruby  #ruby-on-rails 

WordsCounted: A Ruby Natural Language Processor

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.

Features

• Out of the box, get the following data from any string or readable file, or URL:
  • Token count and unique token count
  • Token densities, frequencies, and lengths
  • Char count and average chars per token
  • The longest tokens and their lengths
  • The most frequent tokens and their frequencies.
• A flexible way to exclude tokens from the tokeniser. You can pass a string, regexp, symbol, lambda, or an array of any combination of those types for powerful tokenisation strategies.
• Pass your own regexp rules to the tokeniser if you prefer. The default regexp filters special characters but keeps hyphens and apostrophes. It also plays nicely with diacritics (UTF and unicode characters): Bayrūt is treated as ["Bayrūt"] and not ["Bayr", "ū", "t"], for example.
• Opens and reads files. Pass in a file path or a url instead of a string.

Installation

Add this line to your application's Gemfile:

gem 'words_counted'

And then execute:

$ bundle

Or install it yourself as:

$ gem install words_counted

Usage

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.

API

WordsCounted

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.

Tokeniser

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.

Counter

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

Excluding tokens from the tokeniser

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.

1. A space-delimited string. The filter will normalise the string.
2. A regular expression.
3. A lambda.
4. A symbol that names a predicate method. For example :odd?.
5. An array of any combination of the above.

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"]

Passing in a custom regexp

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"]

Opening and reading files

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")

Gotchas

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.

A note on case sensitivity

The program will normalise (downcase) all incoming strings for consistency and filters.

Roadmap

Ability to open URLs

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.

 

RubyDoc documentation.

Demo

Visit this website for one example of what you can do with WordsCounted.

---

Contributors

See contributors.

Contributing

1. Fork it
2. Create your feature branch (git checkout -b my-new-feature)
3. Commit your changes (git commit -am 'Add some feature')
4. Push to the branch (git push origin my-new-feature)
5. Create new Pull Request

Author: Abitdodgy
Source Code: https://github.com/abitdodgy/words_counted 
License: MIT license

#ruby #nlp 

SafeMoon Clone | Create A DeFi Token Like SafeMoon | DeFi token like SafeMoon

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

SafeMoon Clone | SafeMoon Token Clone | SafeMoon Token Clone Development

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.

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Reasons to invest in SafeMoon Token Clone :

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• The Automated Burning tokens result in the community no longer having control over the SafeMoon tokens. Instead, the community can control the burn of the tokens efficiently for promoting its value in the marketplace. The transaction of SafeMoon tokens on the blockchain platform is fast, safe, and secure.

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.

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All about Google ‘Verse-by-Verse’ | TopDevelopers.co

Google’s Verse by Verse allows the users to rekindle their old love for poetry. By offering innovative suggestions, the software aims to take users to a road less traveled.

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