by SalesforceAIResearch · AI 工具 · ★ 637
[]() Paper | Key Features | -- Model Instruction | Framework | Installation | Train | Benchmarks | Acknowledgement 🎉🎉🎉 News [08-20.2025] 🎉🎉🎉 ActionStudio and LATTE (Learning to think with vision specialists) are both accepted by EMNLP 2025 Main conference! [08-05.2025] 💫 ActionStudio has been updated with new features, improved training configuration tracking, and general code enhancements! [05-12.2025] Our xLAM Presentation Slides for the NAACL 2025 Oral Session are now live! 📂 We’ve also open-sourced APIGen-MT-5k — a compact yet powerful dataset to explore multi-turn...
| Stars | 637 |
| Forks | 60 |
| Language | Python |
| Category | AI 工具 |
| License | Apache-2.0 |
| Quality Score | 61.901189142332/100 |
| Open Issues | 8 |
| Last Updated | 2026-06-02 |
| Created | 2024-02-27 |
| Platforms | python |
| Est. Tokens | ~2504k |
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xLAM is xLAM: A Family of Large Action Models to Empower AI Agent Systems. It is categorized as a AI 工具 with 637 GitHub stars.
xLAM is primarily written in Python. It covers topics such as actionstudio, agents, agentstudio.
You can find installation instructions and usage details in the xLAM GitHub repository at github.com/SalesforceAIResearch/xLAM. The project has 637 stars and 60 forks, indicating an active community.
xLAM is released under the Apache-2.0 license, making it free to use and modify according to the license terms.