Good starting point for working on data science projects. Contains numpy, pandas, matplotlib, tensorflow and more.
Access the OpenAI ChatGPT 3.5 Turbo chat AI model using Python.
Access the OpenAI GPT-4 chat AI model using Python. Create your own LLM-driven AI server!
Access the OpenAI GPT-4 chat AI model using Node.js.
UI interface to generate NFTs using Dall-E API then mint and deploy to the blockchain built by Ethan Hasbrouk.
Click "Use template" and signup for an Alchemy account here to get your API key: https://dashboard.alchemy.com/signup/?a=ai-nft-generator-replit-template https://dashboard.alchemy.com/signup/?a=ai-nft-generator-replit-template
(You will need to input your own Open AI and Pinata API keys for the replit to run).
Use this template to create your own prompt app with GPT. This template provides the tools you need to build, deploy, and invoke a production-ready prompt app.
Access the OpenAI Whisper Speech-to-Text AI model using Python.
Make a custom AI writer with a few lines of code!
This Repl uses Cohere AI's language models to generate custom text based on a given "command". It can be adapted to any text generation use-case by adjusting the prompt.
This example generates a short story about learning to code :)
For those interested in forking, you can get a free API key here: https://dashboard.cohere.ai/welcome/register?utm_source=other&utm_medium=social&utm_campaign=nicks-repl
This Repl is a template for creating AI-Enabled applications, like 'ChatGPT for my data' with an embeddings store and large language models.
Starter code for using Hugging Face's Transformers pipelines feature to set up an ML inference pipeline for NLP tasks.
🌟 Learn to train ML models in the Replit x Weights & Biases Hackathon from February 4th - 11th 🌟
Fork this repl and run it to get started with basic machine learning with Weights & Biases
Weights & Biases is a machine learning experiment tracking, model checkpointing and data visualisation tool used by over 200,000 ML practitioners across the world.
Running this repl will::
Run some dummy logging to show the basics of logging to Weights & Biases
Run a mini-experiment varying the amount of Dropout in your model and logging the results to Weights & Biases
To log results to your own Weights & Biases account, create an account at the link below, then enter your API key when prompted. Otherwise just select the option to log anonymously, without entering an API key.
Sign up to Weights & Biases here to get started!
Gradio is a Python library that allows you to quickly build web-based machine learning demos, data science dashboards, or other kinds of web apps, entirely in Python. This demo uses the integration of Gradio with the Hugging Face Inference api to load a model and launch an interface.