概要
Eagleは、NVIDIAが提供する最先端のビジュアル言語モデルシリーズであり、マルチモーダル理解、長文脈推論、具現化AIを実現するためのデータ駆動型戦略を探求しています。複数のバージョンが含まれており、汎用的な位置特定、検出、動画理解などのタスクをサポートしています。
README プレビュー
\n\n# 🦅 Eagle: Frontier Vision-Language Models with Data-Centric Strategies\n\n\n \n\n\n[](LICENSE)\n[](./Eagle2_5/LICENSE_MODEL)\n\n[[📘Eagle Report](Eagle/Eagle.pdf)] [[📘Eagle 2 Report](Eagle2_5/Eagle2.pdf)] [[📘Eagle 2.5 Report](Eagle2_5/Eagle2.5.pdf)] [[📘LocateAnything Report](https://research.nvidia.com/labs/lpr/locate-anything/LocateAnything.pdf)]\n\n[[🤗Model Collection](https://huggingface.co/collections/nvidia/eagle)] [[🤗LocateAnything Demo](https://huggingface.co/spaces/nvidia/LocateAnything)] [[🌐Project Page](https://nvlabs.github.io/Eagle/)]\n\n\n\n\n## Updates\n- [2026/06] 🎉 LocateAnything is accepted to [ECCV 2026](https://eccv.ecva.net/).\n- [2026/06] 🔥 Release [visual prompt fine-tuning script](./Embodied/shell/locate-anything-lora-visual-prompt.sh) for LocateAnything with LoRA fine-tuning.\n- [2026/06] 🔥 LocateAnything now supports [batch inference](./Embodied/) with a pure FlashAttention runtime — efficient inference on A100, RTX 4090, and other non-Hopper/Blackwell GPUs.\n- [2026/05] 🔥 Release [LocateAnything](./Embodied/) — A generalist vision-language grounding model based on Eagle.\n- [2025/12] 🎉 A native resolution variant of the Eagle model is adopted as the VLM backbone of [GR00T-N1.6](https://huggingface.co/collections/nvidia/gr00t-n16). Check out the [tech blog](https://research.nvidia.com/labs/gear/gr00t-n1_6/) for more details.\n- [2025/10] 🔥 Release Eagle 2.5 [source code](https://github.com/NVlabs/EAGLE/tree/main/Eagle2_5).\n- [2025/09] 🔥 Eagle 2.5 is accepted to [NeurIPS 2025](https://neurips.cc/Conferences/2025).\n- [2025/09] 🎉 Eagle 2 is supported in [Torch-TRT](https://github.com/pytorch/TensorRT/tree/main/tools/llm).\n- [2025/07] 🎉 Release Eagle 2.5 [model](https://huggingface.co/nvidia/Eagle2.5-8B).\n- [2025/06] 🔥 Eagle 2.5 is adopted as the VLM backbone of [GR00T-N1.5](https://huggingface.co/nvidia/GR00T-N1.5-3B). Check out the [tech blog](https://research.nvidia.com/labs/gear/gr00t-n1_5/) for more details.\n