Improved Retrieval Augmented Generation with ALL-SORT - Advanced Techniques
Explore advanced retrieval augmented generation techniques using ALL-SORT for improved LLM-assisted information retrieval, with practical demonstrations and performance evaluations.
Combined Preference and Supervised Fine-Tuning with ORPO
Explore combined preference and supervised fine-tuning with ORPO. Learn about fine-tuning methods, loss functions, and performance improvements. Includes practical demos and evaluations.
Full Fine-Tuning vs LoRA and QLoRA - Comparison and Best Practices
Explore full fine-tuning vs (Q)LoRA techniques, comparing VRAM usage, training time, and quality. Learn parameter selection, tips for QLoRA, and step-by-step guidance for TinyLlama and Mistral 7B fine-tuning.
Tiny Text and Vision Models - Fine-Tuning and API Setup
Explore fine-tuning and API setup for tiny text and vision models, covering multi-modal architectures, LoRA adapters, and deployment strategies for custom APIs.
Very Few Parameter Fine-Tuning with ReFT and LoRA
Explore advanced fine-tuning techniques ReFT and LoRA for efficient parameter optimization in transformer models. Learn implementation, comparison, and practical tips for improved model performance.
Transformers from Scratch - Part 2: Building and Training a Weather Prediction Model
Dive deep into advanced transformer concepts, exploring encoder-decoder architectures, GPT-4o, and positional embeddings. Apply knowledge to weather prediction and analyze model performance.
Fine-tuning Llama 3 on Wikipedia Datasets for Low-Resource Languages
Learn to fine-tune Llama 3 on Wikipedia datasets for low-resource languages. Master dataset creation, LoRA setup, blending techniques, and parameter optimization for improved language model performance.
Preparing Fineweb - A Finely Cleaned Common Crawl Dataset for Language Models
Explore Common Crawl data processing, comparing datasets like C4 and RefinedWeb. Learn about quality filters, deduplication strategies, and LLM-assisted filtering for creating high-quality datasets like Fineweb Edu.
Improving LLM Accuracy with Monte Carlo Tree Search
Explore Monte Carlo Tree Search to enhance LLM accuracy, focusing on boosting Llama 3 8B performance. Learn implementation, testing, and limitations through code examples and mathematical problem-solving.
RAG with Verified Citations - Advanced Inference Techniques
Explore advanced RAG techniques with verified citations, including BM25 and cosine similarity methods. Learn to implement and leverage one-click document RAG for improved accuracy.
Fine-Tuning a Diffusion Model with Your Photos
Learn to fine-tune a diffusion model using your own photos. Explore Flux Schnell, set up GPU environments, create datasets, and understand the intricacies of diffusion models and their architectures.
The Magic of Merlin - Shopify's New Machine Learning Platform
Explore Shopify's Merlin ML platform, its open-source stack, architecture, and how it scales ML work using Ray.
Predibase: A Low-Code Deep Learning Platform Built for Scale
Explore Predibase: a low-code deep learning platform combining large-scale ML with state-of-the-art architectures for NLP, computer vision, and tabular data, built on Ludwig and Ray for scalable, end-to-end solutions.
Scalable Training of Language Models Using Ray, JAX, and TPUv4
Explore challenges and design decisions for scalable language model training, with quantitative analysis of efficiency improvements using Ray, JAX pjit, and TPUv4.
Hugging Face and Ray AIR Integration for Scalable Machine Learning
Explore Hugging Face and Ray AIR integration for scalable model training and data loading. Learn to create end-to-end workflows from data ingest to inference and serving.
Scalable Feature Engineering with Hamilton on Ray
Explore scalable feature engineering using Hamilton and Ray at StitchFix. Learn declarative dataflow, team scaling, and efficient computation for thousands of time-series features.
FastCFE - A Counterfactual Explainer Using Reinforcement Learning
Explore reinforcement learning for real-time counterfactual explanations in machine learning explainability. Learn about FastCFE algorithm, OpenAI Gym, and Ray+RLlib for actionable insights in various applications.
KubeRay - A Kubernetes Ray Clustering Solution
Explore KubeRay, an open-source toolkit for managing Ray clusters on Kubernetes. Learn about architectural decisions, resource management, job submission, and autoscaling capabilities.
Alpa: Simple Large Model Training and Inference on Ray
Explore Alpa, a Ray-native library for automated model-parallel training of large deep learning models, optimizing execution plans and scaling complex architectures efficiently.
Gearing Up for FIFA 2022 Using RLlib-Powered Traffic Control
Optimize traffic control for FIFA 2022 using RLlib-powered multi-agent reinforcement learning, microsimulation, and Graph Convolutional Networks for congestion management in Qatar.
Cruise.data - A New Dataset Processing Pipeline for Cruise ML
Explore Cruise.data, a novel ML data pre-processing framework combining tf.data, PyTorch, and large-scale processing capabilities for efficient and scalable dataset handling in autonomous vehicle development.