Resource library
Evaluating Coding Agent Capabilities with Terminal-Bench: Snorkel’s Role in Building the Next Generation Benchmark
Closing the Evaluation Gap in Agentic AI
Announcing a $3M commitment to launch Open Benchmarks Grants
Benchtalks #1: Alex Shaw (Terminal-Bench, Harbor) – Building the Benchmark Factory
Building FinQA: An Open RL Environment for Financial Reasoning Agents
The Snorkel Flow label model plays an instrumental role in driving the enterprise value we create. Here’s a peek at how it works.
Learn how Alfred enables users to encode their subject matter expertise via natural language prompts for language and vision-language models.
Vision language models demonstrate impressive image classification capabilities, but LLMs can help improve their performance. Learn how.
Learn how to fine-tune LLMs like Meta’s Llama 3 for specialized tasks and see a live demo of curating high-quality training data with Snorkel Flow
Snorkel researchers devised a new way to evaluate long context models and address their “lost-in-the-middle” challenges with mediod voting.
See a walkthrough of how Snorkel Flow users build applications with production-grade RAG retrieval components.
Learn how to optimize RAG components to increase accuracy with programmatic data development in this free webinar.
Fine-tuning specialized LLMs demands a lot of time and cost We developed Bonito to make this process faster, cheaper, and easier.
