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CryptoUnits - 1539+ Best Cryptocurrency Websites & Bitcoin Sites List of 2023!

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Cryptocurrency Forensics 🚀🌑

Pepe AI

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Contact Us for Delisting

If your website has been listed as potentially fraudulent, but you believe that it is not involved in any deceptive activities, please reach out to us.

Once you've furnished us with compelling evidence of your legitimate presence in the Crypto World, we will consider removing your website from the list.

Common Reasons for Listing

We typically categorize websites as potentially fraudulent for several reasons:

  • You may be concealing your team's identity.
  • Your website might have a negative reputation due to suspicions of trickery or scams.
  • You may lack a well-crafted project whitepaper, or the existing one may be of poor quality.

Their official site text


Pepe the Frog (/ˈpɛpeɪ/) is a cartoon character and Internet meme created by cartoonist Matt Furie. Designed as a green anthropomorphic frog with a humanoid body, Pepe originated in Furie's 2005 comic Boy's Club. The character became an Internet meme when his popularity steadily grew across websites such as Myspace, Gaia Online, and 4chan in 2008.

Pepe is tired of watching everyone play hot potato with the endless derivative ShibaCumGMElonKishuTurboAssFlokiMoon Inu coins. The Inu’s have had their day. It’s time for the most recognizable meme in the world to take his reign as king of the memes.

Pepe is here to make memecoins great again. Launched stealth with no presale, zero taxes, LP locked and contract renounced, $PEPEAI is a coin for the people, forever. Fueled by pure memetic power, let $PEPE show you the way.

$pepeai coin has no association with Matt Furie or his creation Pepe the Frog. This token is simply paying homage to a meme we all love and recognize.

$PEPEAI is a meme coin with no intrinsic value or expectation of financial return. The coin is completely useless and for entertainment purposes only.


All jokes aside, here is a rough sketch of $pepe path ahead.

We don't want to give everything away on day 1, Expect surprises along the way ;)

Phase 1

  • CoinGecko and CoinMarketCap Listing
  • 6900 $PepeAI holders
  • Twitter Promotion
  • CoinZilla Marketing
  • Media release on Yahoo, Bloomberg,
  • TrustWallet, TokenPocket Update

Phase 2

  • 42,690 $PepeAI Holders
  • Targeted Airdrop Campaign
  • CEX Listing
  • Community Partnerships Pepe Times digital newsletter
  • Banners and Billboards in New York, UAE

Phase 3

  • 1M $PepeAI Holders
  • Celebrity Partnership
  • T1 Exchange Listings
  • Meme Takeover
  • Security & Audit
  • Contract ownership Renounced

Liquidity Locked

The concept of liquidity locking was developed to ensure that pool tokens cannot be moved or redeemed until a pre-specified amount of time has elapsed. This helps give users assurance in the market they are investing in since they know the pool tokens cannot be moved during the specified time period. To ensure that the liquidity locking process is correctly implemented, standards have been put in place to verify that it was correctly done, alongside easy-to-use tools that anyone can use.

Contract Audit

A thorough examination of the code of a smart contract is conducted in an audit, to uncover security flaws, inaccurate or inefficient programming, and methods to increase its solidity. By carrying out an audit, developers are enabled to guarantee the safety and dependability of their blockchain applications.


Supply of 69 Trillions (69,000,000,000,000) $PepeAI

Buy / Sell Tax: ZERO

No Taxes, No Bullshit. It’s that simple.


  • 72.3% added to PancakeSwap
  • 24.5% burn to 0x00000000dead
  • 1.1391% at
  • 1.0061% at Huobi
  • 0.6097% at Binance Safu Wallet

Pepe is here to make memecoins great again.


Draw PEPE takes the beneficial elements of Dall-E 2 and Latent Diffusion, adding new thoughts as well. It uses the CLIP model to act as the text and image encoder, and also forges a diffusion image prior (mapping) between the latent spaces of the CLIPs. From here, a generative model based on multi-modal VAE is created, which jointly optimizes the log-likelihood of the image and text, whilst taking into consideration the cross-modal correlations.

We use a transformer with 20 layers, 32 heads, and a hidden size of 2048 to diffuse the latent spaces in order to enhance the visual performance of the model, providing new opportunities for blending images and manipulating images via text.

By using a deep learning encoder-decoder architecture, Draw PEPE is able to transform a simple text description into a visually stunning and accurate rendition of what the user is describing. Additionally, this system enables the user to adjust the parameters of the output image, thus further customizing their masterpiece.

To show our commitment and dedication to PEPE, Draw PEPE will only accept prompts that include the name "PEPE".

AI Draw PEPE at [link]


Reinforcement Learning from Human Feedback (RLHF)

Using Reinforcement Learning from Human Feedback (RLHF), we fine-tuned our model. We trained a reward model to assess the utterances generated by the model when conversing with humans. This was to identify and correct errors made by the model, as well as to guide it in creating more fruitful conversations. Finally, through the same RLHF, we adjusted the model's parameters to maximize the rewards given by the reward model.

We trained an initial model using a supervised fine-tuning process, and the human-AI trainers were given model-written suggestions to help them create their responses.

We further modified the InstructGPT dataset to be in a dialogue format, thus expanding the range of inputs our model could learn from. Additionally, we used the Reinforcement Learning from Human Feedback (RLHF) algorithm to fine-tune the model’s parameters to make the model's predictions more accurate. To achieve this, a reward model was created to measure the quality of the conversations the model was having with human partners and was used to identify and fix mistakes whilst also enabling us to shape the outputs of our model to be more relevant.

Try ASK PEPE - [link]


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