How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.
This repository is for EleutherAI's project Pythia which combines interpretability analysis and scaling laws to understand how knowledge develops and evolves during training in autoregressive transformers. For detailed info on the models, their training, and their properties, please see our…
🌊 Floom, "The K8s for AI", orchestrates & executes Generative AI pipelines, Empowering Developers and DevOps to focus on what matters.
Arize Phoenix is an LLM observability platform and evaluation framework designed to capture execution traces and monitor large language model applications. It serves as a prompt management system for versioning and testing templates, and as a self-hosted AI operations infrastructure for managing telemetry and experiments. The platform differentiates itself through a specialized embedding visualization tool used to detect data drift and optimize vector search. It provides a comprehensive evaluation suite that utilizes judge-based evaluators and ground-truth datasets to score model outputs, and
The main features of clarkkev/attention-analysis are: Model Analysis Tools.
Open-source alternatives to clarkkev/attention-analysis include: bizarrecake/fmr.ai. eleutherai/pythia — This repository is for EleutherAI's project Pythia which combines interpretability analysis and scaling laws to… floomai/floom — 🌊 Floom, "The K8s for AI", orchestrates & executes Generative AI pipelines, Empowering Developers and DevOps to focus… floriandietz/comgra. inseq-team/inseq. arize-ai/phoenix — Arize Phoenix is an LLM observability platform and evaluation framework designed to capture execution traces and…