Making large AI models cheaper, faster and more accessible
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Updated
Apr 2, 2023 - Python
Making large AI models cheaper, faster and more accessible
Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
EVA Series: Vision Foundation Model Fanatics from BAAI
Interactive data structures for indexing unstructured data with foundation models.
InternVideo: General Video Foundation Models via Generative and Discriminative Learning (https://arxiv.org/abs/2212.03191)
Official Code for "Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents"
PyTorch implementation of BEVT (CVPR 2022) https://arxiv.org/abs/2112.01529
This repository holds code and other relevant files for the NeurIPS 2022 tutorial: Foundational Robustness of Foundation Models.
Self-supervised learning for wearables using the UK-Biobank (>700,000 person-days)
Official implementation for CVPR'23 paper "BlackVIP: Black-Box Visual Prompting for Robust Transfer Learning"
FEMR (Framework for Electronic Medical Records) provides tooling for large-scale, self-supervised learning using electronic health records
MelXior: a Neural Weather Forecasting app distilling knowledge from models including GPT-3, DALL-E and FourCastNet
Object Detection with Vision-Language Pre-training
Simple Image Search powered by Multimodal Foundation Models (OpenAI Clip and Microsoft GLIP)
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