Replit Code v1.5 is a 3.3B parameter Causal Language Model focused on Code Completion. The model is trained in bfloat16 on 1T tokens of code (~200B tokens over 5 epochs, including linear cooldown) for 30 programming languages
This is an impressive AI model that was released this past weekend at the AI Engineer Summit in San Francisco. The results are pretty solid — don't sleep on this.
This project seems promising to me, congratulations to the developers! I'm excited to see where this goes
Replit's decision to make AI free for all users is commendable and reflects the growing importance of AI in software development. The new code generation language model, Replit Code V1.5 3B, looks promising, especially with its open-source approach. It's great to see AI becoming more accessible to the developer community. Thanks for sharing this update!
Replit Code v1.5 is every coder's dream! Code completion to the next level. Bring it on!
Remarkable achievement, congratulations!
Might be of interest: @naoto_shibata_morph, @oginokairan.
Impressive launch! 🚀 Good luck with your project! 🌟
How does your model handle complex code suggestions for multiple programming languages?
About Replit Code V1.5 3B on Product Hunt
“A new code generation language model”
Replit Code V1.5 3B launched on Product Hunt on October 13th, 2023 and earned 118 upvotes and 13 comments, placing #21 on the daily leaderboard. Replit Code v1.5 is a 3.3B parameter Causal Language Model focused on Code Completion. The model is trained in bfloat16 on 1T tokens of code (~200B tokens over 5 epochs, including linear cooldown) for 30 programming languages
Replit Code V1.5 3B was featured in Developer Tools (511.3k followers), Artificial Intelligence (466.7k followers) and Development (5.8k followers) on Product Hunt. Together, these topics include over 157.5k products, making this a competitive space to launch in.
Who hunted Replit Code V1.5 3B?
Replit Code V1.5 3B was hunted by Chris Messina. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Chris Messina