Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Collection of prompt patterns, experiments, and research around agentic AI workflows and prompting strategies.
The AI Scientist: Towards Fully Automated Open-Ended Scientific.
A super-easy way to record, search and compare 1000s of ML training runs.
Easy way to turn any app into searchable data for LLMs.
Easy to use Neural Search Engine. Index latent vectors along with JSON metadata and do efficient k-NN search.
Platform for Neural Network Search (NAS) that allows you to generate efficient deep networks for your applications.
Automatic architecture search and hyperparameter optimization for PyTorch.
AI Native database for embedding vectors.
Latest Papers and Datasets on Multimodal Large Language Models, and Their Evaluation.
A PyTorch implementation of CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation".
Basic proof of concept for genetic architecture search in Keras.
Example of RAG architecture using semantic search and summarization for retrieving Bible passages.
ImageBind One Embedding Space to Bind Them All.
Foundational Models for State-of-the-Art Speech and Text Translation.
Framework for building applications with LLMs and Transformers (e.g. agents, semantic search, question-answering).
Implementation of image to image (pix2pix) translation from the paper by isola et al.[DEEP LEARNING].
AI-native database built for LLM applications, providing incredibly fast vector and full-text search.
A project to make it easier to use large external knowledge bases with LLMs.
PyTorch Meta-learning Framework for Researchers.
Universal memory service with semantic search, autonomous consolidation, and multi-client support for AI applications.