Replit — How to train your own Large Language Models
2023年4月18日 · At Replit, we've invested heavily in the infrastructure required to train our own Large Language Models from scratch. In this blog post, we'll provide an overview of how we train LLMs, from raw data to deployment in a user-facing production environment.
Replit — Productizing Large Language Models
We can train LLMs to break such loop of repetitions by penalizing repetitions on synthetic data. Finetuning on user feedback: We can use feedback from users to finetune the model to better match the user's preferences.
Get Started with LLMs: AI Camp x Replit Course Now Available
2023年3月9日 · Gitless and instant, from start to running LLM App in the first 15 minutes. Replit and AI Camp are launching a brand new, 4-hour course, right here on Replit! Unlock the Power of LLMs like GPT with Python, is a four-lesson course that’ll teach you: How to access AI APIs Implementing GPT-2 Trade up to Gradio, Flan-T5 and GPT-3 Build your own ...
Replit — Building LLMs for Code Repair
2024年4月2日 · To create the repaired code, we follow a two-step approach: we first use a SOTA LLM to create a fix for the (code, diagnostic) pair, and a human annotator verifies that the solution is correct. If it isn't the annotator provides a correct fix.
Replit — How Replit makes sense of code at scale
2024年8月14日 · We can also discover untapped potential in certain external integrations with third-party tools, like with LLM providers. It informs our growth and sales strategy while supporting our anti-abuse efforts. And, of course, it allows us to train powerful AI models.
Replit — BerriAI—The Y Combinator company that brings LLM …
2023年3月6日 · BerriAI is a Y Combinator-backed company that lets users build production-ready ChatGPT apps in under 2 minutes by easily connecting your data to an LLM. With BerriAI you can spin up a ChatGPT app for: Customer support trained on your Knowledge Base and FAQs Answering questions related to your internal knowledge base Analyzing Product data (on ...
Replit — Everything you need to know about MCP
2025年3月8日 · llm "Summarize this video https://youtu.be/1qxOcsj1TAg and write the summary to summary.txt" Most people can set up in under five minutes. MCP supports multiple programming languages including Python, TypeScript, Java, and others. Whether you're creating new services or using existing ones, there's a path for you. Core Capabilities
Replit + Weights & Biases: Building a RAG Bot
2023年11月29日 · Weights & Biases (W&B) provides AI developers with powerful tools to build better models faster and is used by almost every top LLM research lab today. To help support internal and external users, W&B built WandBot – a question-answering bot built on the robust llama-index library and the intelligence of OpenAI's GPT-4.
Replit — From localhost to live
2024年10月8日 · The Agent is a LLM interface that has access to the entire Replit workspace. The Agent differs from other AI coding tools: it creates entire development environments. That means installing languages and packages, adding services, and even deploying your apps.
Replit — Announcing Replit AI for All
Emboldened by the strong performance we obtained with training and serving replit-code-v1-3b, today we are also releasing replit-code-v1.5-3b, a state-of-the-art 3B LLM trained on 1T tokens from a code-heavy pretraining mixture. The dataset includes 30 programming languages and a dev-oriented subset of StackExchange.