Kwai-Keye/Keye-VL-1_5-8B 已完整同步
Kwai Keye-VL 1.5
Keye-VL-1.5 is a cutting-edge Multimodal Large Language Model (MLLM) that addresses fundamental challenges in video comprehension. It features a novel Slow-Fast video encoding strategy, a progressive four-stage pre-training methodology to extend context length up to 128K tokens, and a comprehensive post-training pipeline focusing on reasoning enhancement and human preference alignment. The model demonstrates significant improvements in video understanding tasks and maintains competitive performance on general multimodal benchmarks.
🔥 News
2025.08.28🌟 We are excited to introduce Kwai Keye-VL-1.5, a more powerful version! By incorporating innovativeSlow-Fast Video Encoding strategy,new LongCoT Cold-Start data pipeline, andadvanced RL training strategies, Keye-VL-1.5 reaches new heights in video understanding, image comprehension, and reasoning capabilities. Plus, it now supports an extended context length of up to 128k tokens for handling longer conversations and complex tasks. Stay tuned for more groundbreaking innovations!2025.07.08🌟 Keye-VL is supported by swift and vLLM. Feel free to use it without hesitation!2025.07.03🌟 We are excited to announce the release of our comprehensive technical report! You can read it now at arxiv.2025.06.26🌟 We are very proud to launch Kwai Keye-VL, a cutting-edge multimodal large language model meticulously crafted by the Kwai Keye Team at Kuaishou. As a cornerstone AI product within Kuaishou's advanced technology ecosystem, Keye excels in video understanding, visual perception, and reasoning tasks, setting new benchmarks in performance. Our team is working tirelessly to push the boundaries of what's possible, so stay tuned for more exciting updates!
Contents
- Kwai Keye-VL 1.5
- 🔥 News
- 📐 Quick Start
- Preprocess and Inference
- Install
- Keye-VL-1.5 Inference
- Deployment
- Install
- Offline Inference
- Online Serving
- Evaluation
- Preprocess and Inference
- 👀 Architecture and Training Strategy
- 🌟 Pre-Train
- 🌟 Post-Train
- 📈 Experimental Results
- ✒️ Citation
- Acknowledgement
📐 Quick Start
Preprocess and Inference
See keye-vl-utils/README.md for details. Keye-vl-utils contains a set of helper functions for processing and integrating visual language information with Keye Series Model.
Install
pip install --upgrade keye-vl-utils==1.5.2 -i https://pypi.org/simple
Keye-VL-1.5 Inference
from transformers import AutoModel, AutoTokenizer, AutoProcessor
from keye_vl_utils import process_vision
36 个文件
浏览文件数据集版权信息
本数据集的许可证为 Apache License 2.0。如有违反相关条款,请联系 WEHUB,我们将及时处理。 查看许可证
通过 WeHub CLI 下载当前数据集快照。下列命令会固定为当前页面展示的数据版本(如果页面提供版本)。文件字节由本机直连存储下载,浏览器不会签发或保存下载链接。
前置要求
需要 Node.js 18 及以上,以及 npm(或 npx)。
1. 安装 CLI
npm install -g wehub-cli@latest
2. 下载此数据集
wehub datasets download ds_ext_4062_9ceb537c71 --revision b4d413e4f42a3999af1f5ba0e281c7d51d6b93de --output ./ds_ext_4062_9ceb537c71
若中断或部分失败,在同一目录重新执行同一命令即可续传。默认会校验 SHA-256。
免全局安装
npx --yes wehub-cli@latest datasets download ds_ext_4062_9ceb537c71 --revision b4d413e4f42a3999af1f5ba0e281c7d51d6b93de --output ./ds_ext_4062_9ceb537c71
高级选项
以下为 wehub datasets download 已支持的参数示例:
强制重新下载,不复用已校验的本地文件
wehub datasets download ds_ext_4062_9ceb537c71 --revision b4d413e4f42a3999af1f5ba0e281c7d51d6b93de --output ./ds_ext_4062_9ceb537c71 --overwrite
仅包含匹配路径
wehub datasets download ds_ext_4062_9ceb537c71 --revision b4d413e4f42a3999af1f5ba0e281c7d51d6b93de --output ./ds_ext_4062_9ceb537c71 --include "*.jsonl"
排除匹配路径
wehub datasets download ds_ext_4062_9ceb537c71 --revision b4d413e4f42a3999af1f5ba0e281c7d51d6b93de --output ./ds_ext_4062_9ceb537c71 --exclude "*.md"
提高并发下载数
wehub datasets download ds_ext_4062_9ceb537c71 --revision b4d413e4f42a3999af1f5ba0e281c7d51d6b93de --output ./ds_ext_4062_9ceb537c71 --jobs 8
完整帮助:wehub datasets download --help