cloneofsimo/lora
Using Low-rank adaptation to quickly fine-tune diffusion models.
https://github.com/cloneofsimo/lora.gitSignal Finder is an independent product. Some AI-powered features use third-party AI models to generate summaries, search assistance, and research outputs. Model providers do not operate, endorse, or control Signal Finder.
AI outputs may be inaccurate, incomplete, or outdated. Please review the original repository, documentation, and your own judgment before making product, technical, or business decisions.
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
The 'ML-For-Beginners' project is a 12-week, 26-lesson curriculum on classic machine learning using Scikit-learn, with quizzes and projects. It supports multiple languages and is designed for self-paced learning on GitHub, with a focus on building skills through practical application.
Develop an interactive, subscription-based online learning platform that integrates the ML-For-Beginners curriculum with real-world project examples and mentorship. Differentiate by offering personalized learning paths and industry-relevant case studies.
21 Lessons, Get Started Building with Generative AI
21 Lessons teaching everything you need to know to start building Generative AI applications 🌐 Multi-Language Support Supported via GitHub Action (Automated & Always Up-to-Date) Arabic | Bengali | Bulgarian | Burmese (Myanmar) | Chinese (Simplified) | Chinese (Traditional, Hong Kong) | Chinese (Traditional, Macau) | C
Focus on one document-heavy or ops-heavy job and make the path from raw context to useful answer dramatically shorter.
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
Build a Large Language Model (From Scratch) This repository contains the code for developing, pretraining, and finetuning a GPT-like LLM and is the official code repository for the book Build a Large Language Model (From Scratch). In *Build a Large Language Model (From Scratch)*, you'll learn and understand how large l
Build a single-purpose inference service optimized for one model family with better defaults and lower ops overhead.
The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.
Grafana is an open-source observability platform for visualizing metrics, logs, and traces from various sources like Prometheus, Loki, and Elasticsearch. It offers dynamic dashboards, ad-hoc metric exploration, log analysis, alerting, and supports mixed data sources on a per-query basis. Grafana is designed for browser-based use and is compatible with Slack and other notification systems.
Build a targeted analytics dashboard for cloud-based application performance monitoring. Specifically, create a Grafana-based product that focuses on AWS and Azure cloud services, offering pre-built dashboards and integrations with cloud metrics and logs. Differentiate from existing solutions by providing a seamless experience for cloud-native applications and by offering a subscription model that includes premium support and updates.
Examples and guides for using the OpenAI API
The OpenAI API Cookbook provides example code and guides for using the OpenAI API, requiring an OpenAI account and API key. It includes Python examples and is applicable across various languages. The project is licensed under the MIT License.
Develop a subscription-based AI development platform that provides curated examples, tutorials, and support for the OpenAI API. Target niche markets such as educational institutions and startups by offering a unique blend of ready-to-use code snippets, comprehensive documentation, and personalized support. Differentiate from existing solutions by providing a more user-friendly interface and a focus on real-world application examples.