Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
A high-performance framework for training LLMs, VLMs, diffusion, and embodied models on NVIDIA GPUs and Kunlun XPUs. Supports Pi0.5, GR00T-N1.7, FastWAM, Cosmos3, DreamZero, DeepSeek-V4, GLM-5.3, Kimi-K3 and more.
🚀 Pytorch Distributed native training library for LLMs/VLMs with OOTB Hugging Face support
MLX-VLM is a package for inference and fine-tuning of Vision Language Models (VLMs) on your Mac using MLX.
Multimodal visual memory agent on macOS
NVIDIA AI Blueprint for video search and summarization (VSS) is a GPU-accelerated reference architecture for building video analytics agents with real-time verified alerts, visual Q&A, and automated reporting. The VSS Blueprint uses vision language models (VLMs) such as NVIDIA Cosmos, LLMs such as NVIDIA Nemotron, RAG, and NVIDIA NIMs.
Awesome-Jailbreak-on-LLMs is a collection of state-of-the-art, novel, exciting jailbreak methods on LLMs. It contains papers, codes, datasets, evaluations, and analyses.
Run frontier LLMs and VLMs locally on Qualcomm devices across NPU, GPU, and CPU with a few lines of code
PTQ-Level Efficiency, QAT-Level Accuracy | 训练后量化的效率,量化感知训练的精度
PhysBrain 1.5: From General VLMs to Physical Foundation Model
HunyuanOCR-1.5: Making Lightweight OCR VLMs Faster and Better
Resources and paper list for "Thinking with Images for LVLMs". This repository accompanies our survey on how LVLMs can leverage visual information for complex reasoning, planning, and generation.
LLMs and VLMs with MLX Swift
Inference engine for Intel devices. Serve LLMs, VLMs, Whisper, Kokoro-TTS, Embedding and Rerank models over OpenAI endpoints.
High-performance Inference and Deployment Toolkit for LLMs and VLMs based on PaddlePaddle
Open-source LLM/VLM load balancer and serving platform for self-hosting LLMs (and VLMs) at scale 🏓🦙 Alternative to projects like llm-d, Docker Model Runner, etc but with less moving parts and simple deployments built around ggml ecosystem. Runs on CPU and GPU.
AI Inference Operator for Kubernetes. The easiest way to serve ML models in production. Supports VLMs, LLMs, embeddings, and speech-to-text.
A library of experiments using frontier LLMs/VLMs for robotics tasks, currently focusing on GPT-6 Astra.
Deferred Exposure of Future Trajectories for Verifiable Reasoning in Autonomous Driving VLMs
A supernode-native post-training engine for rapidly adapting and training LLMs & VLMs
Unified reproductions, benchmarking & evaluation for perception-aware RLVR and OPD in VLMs. 19 methods · 30+ benchmarks · Official code of CGPO (ACM MM 2026 Oral).