Documentation for Fine Tuning Guide, covering setup, features, and practical usage.
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PyTorch Lightning extension that accelerates and enhances foundation model experimentation with flexible fine-tuning schedules.
Finds accurate ML models automatically, efficiently and economically.
Easy-to-use and flexible AutoML library for Python.
This basically to gauge the understanding of Machine Learning Workflow and Regression technique in specific.
Discover Gensbot, where AI meets creativity to offer you personalized printed merchandise for gifts and branding.
Right now, ChatGPT, Perplexity, Claude, and Gemini are answering questions about your industry. They.
Testing framework dedicated to ML models, from tabular to LLMs. Detect risks of biases, performance issues and errors in 4 lines of code.
AI code reviewer for GitHub Actions or local use, compatible with any LLM and integrated with Jira/Linear.
Cloud-Native LLM Routing Engine. Improve LLM app resilience and speed.
Fast and convenient feature processing for low latency machine learning in Go.
Package for computer vision using OpenCV 4 and beyond.
"a collaborative benchmark intended to probe large language models and extrapolate their future capabilities".
GPT Mobile is an Android app that can chat with multiple LLMs at once! Currently supports ChatGPT, Anthropic Claude, and Google Gemini.
Generate & monitor API keys, track usage, and manage Extract/Crawl end-points – all in one place.
GPT-4 Examples, Demos, Apps, Showcase, and Generative AI Use-cases.
GPU cluster manager for running and managing LLMs.
Documentation for Grit, covering setup, features, and practical usage.
An LLM by xAI with open source and open weights. opensource.
A library for developing and comparing reinforcement learning algorithms (successor of [gym])(https://github.com/openai/gym).
Run LLM backends, APIs, frontends, and services with one command.
Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained.
Distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
Making large AI models cheaper, faster and more accessible.