MiniMind-V is an open-source tiny visual-language model (VLM) project that demonstrates how to train a 26M-parameter multimodal VLM from scratch quickly and cheaply (example: ~1 hour / single 3090 GPU and very low rental cost). The repo provides end-to-end code for data cleaning, pretraining, supervised fine-tuning (SFT), evaluation and demo, using CLIP as the visual encoder and MiniMind as the base LLM.
[next-mdx-remote-client] error compiling MDX: Unexpected character `~` (U+007E) before name, expected a character that can start a name, such as a letter, `$`, or `_` More information: https://mdxjs.com/docs/troubleshooting-mdx
Isaac Lab is an open-source, GPU-accelerated robotics learning framework built on NVIDIA Isaac Sim. It provides high-fidelity physics and sensor simulation, ready-to-train environments and robot models, and integrations for reinforcement and imitation learning workflows to accelerate sim-to-real research and large-scale robot training.
