Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)

Inference code for Llama models

A playbook for systematically maximizing the performance of deep learning models.

Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities

Companion webpage to the book "Mathematics For Machine Learning"

EasyR1: An Efficient, Scalable, Multi-Modality RL Training Framework based on veRL

Open-source AI cookbook

Leetcode for Pytorch

Official implementation of BLIP3o-Series

SSSegmentation: An Open Source Supervised Semantic Segmentation Toolbox Based on PyTorch.

Collection of LaTeX resources and examples.

🧀 Code and models for the ICML 2023 paper "Grounding Language Models to Images for Multimodal Inputs and Outputs".

[T-PAMI] A curated list of self-supervised multimodal learning resources.

[ICML 2024] Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models.

[ICLR 2023 spotlight] MEDFAIR: Benchmarking Fairness for Medical Imaging

[ICLR 2025] VL-ICL Bench: The Devil in the Details of Multimodal In-Context Learning

conST: an interpretable multi-modal contrastive learning framework for spatial transcriptomics

Counterfactual Reasoning VQA Dataset

Implementation of "Meta Omnium: A Benchmark for General-Purpose Learning-to-Learn"

[ICML 2024] Fool Your (Vision and) Language Model With Embarrassingly Simple Permutations

Benchmarking Multi-Image Understanding in Vision and Language Models