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© Copyright 2023 XLANG Lab. All right reserved.
We are excited to announce Lemur, an openly accessible language model optimized for both natural language and coding capabilities to serve as the backbone of versatile language agents.
Introducing XLang, an open-source platform that constructs language model agents through executable language grounding. Alongside this framework, we unveil demos of XLang Agents, encompassing Data, Plugins, and Web agents. Moving forward, we're set to open-source multiple substantial projects, encompassing frameworks, models, demos, code, benchmarks, and beyond.
We are excited to announce Lemur, an openly accessible language model optimized for both natural language and coding capabilities to serve as the backbone of versatile language agents.
Introducing XLang, an open-source platform that constructs language model agents through executable language grounding. Alongside this framework, we unveil demos of XLang Agents, encompassing Data, Plugins, and Web agents. Moving forward, we're set to open-source multiple substantial projects, encompassing frameworks, models, demos, code, benchmarks, and beyond.
TLDR: 🎉 Introducing Lemur-70B & Lemur-70B-Chat: 🚀Open & SOTA Foundation Models for Language Agents! The closest open model to GPT-3.5 on 🤖15 agent tasks🤖!
+TLDR: 🎉 Introducing Lemur-70B & Lemur-70B-Chat: 🚀Open & SOTA Foundation Models for Language Agents! The closest open model to GPT-3.5 on 🤖15 agent tasks🤖!
📄Paper: http://arxiv.org/abs/2310.06830
🤗Model: http://huggingface.co/OpenLemur
👩💻Code: https://github.com/OpenLemur/Lemur
@@ -49,4 +49,4 @@There is still much work to be done, but Lemur represents an important step towards open source models that can power the next generation of language agents. We look forward to seeing what the community builds!
You can find more details in our preprint: Lemur: Harmonizing Natural Language and Code for Language Agents
The Lemur project is a open collaborative research effort between XLang Lab and Salesforce Research. We would like to thank Salesforce Research, Google Research, and Amazon AWS for their gift support to this open-source effort!
The Lemur project is a open collaborative research effort between XLang Lab and Salesforce Research. We would like to thank Salesforce Research, Google Research, and Amazon AWS for their gift support to this open-source effort!
+XLANG Lab | <!-- -->Introducing XLang: An Open-Source Framework for Building Language Model Agents via Executable Language Grounding \ No newline at end of file +Blog / XLANG IntroIntroducing XLang: An Open-Source Framework for Building Language Model Agents via Executable Language GroundingAuthorXLANG LabDateAug 10, 2023Share
"Many years later, as he faced the firing squad, Colonel Aureliano Buendía was to remember that distant afternoon when his father took him to discover ice." —— One Hundred Years of Solitude, Gabriel Garcia Márquez.
@@ -75,4 +75,4 @@AcknowledgementsWe would like to express our gratitude towards Google Research, Amazon AWS, and Salesforce Research. The gift funds and necessary computational resources generously provided by these awards have given us the capability and resources to implement this project. We also appreciate the invaluable advice we received throughout the process.
Personal Acknowledgements by Tao:
I feel fortunate for the year I spent at UWNLP, which is one of the world's top institutions for NLP research. During this time, I observed the nascent shift towards LLM in NLP. I would like to extend my thanks to Noah Smith, Luke Zettlemoyer, and Mari Ostendorf. The idea of XLang came about from a suggestion Luke made during a meeting in his office.
-I would also like to pay tribute to my late Ph.D. advisor, Dragomir Radev. Without him, it's very possible that none of what we are starting today would exist.
© Copyright 2023 XLANG Lab. All right reserved.I would also like to pay tribute to my late Ph.D. advisor, Dragomir Radev. Without him, it's very possible that none of what we are starting today would exist.
Our ongoing effort to build an open-source framework and ecosystem for building and evaluating language model agents. The open-source journey begins with XLang Agent demos. In the following months, and beyond, we will be open-sourcing several significant projects, including a framework, models, methods, benchmarks, and more. In the foreseeable future, we envision that a proficient functional agent will require the fusion of these various agents.
Our ongoing effort to build an open-source framework and ecosystem for building and evaluating language model agents. The open-source journey begins with XLang Agent demos. In the following months, and beyond, we will be open-sourcing several significant projects, including a framework, models, methods, benchmarks, and more. In the foreseeable future, we envision that a proficient functional agent will require the fusion of these various agents.
Our ongoing effort to build an open-source framework and ecosystem for building and evaluating language model agents. The open-source journey begins with XLang Agent demos. In the following months, and beyond, we will be open-sourcing several significant projects, including a framework, models, methods, benchmarks, and more. In the foreseeable future, we envision that a proficient functional agent will require the fusion of these various agents.
Our ongoing effort to build an open-source framework and ecosystem for building and evaluating language model agents. The open-source journey begins with XLang Agent demos. In the following months, and beyond, we will be open-sourcing several significant projects, including a framework, models, methods, benchmarks, and more. In the foreseeable future, we envision that a proficient functional agent will require the fusion of these various agents.
We thank the following institutions for their funding support: Google Research, Amazon AWS, Salesforce Research, and UGC.
We thank the following institutions for their funding support: Google Research, Amazon AWS, Salesforce Research, and UGC.
We thank the following institutions for their funding support: Google Research, Amazon AWS, Salesforce Research, and UGC.
We thank the following institutions for their funding support: Google Research, Amazon AWS, Salesforce Research, and UGC.
Welcome to the Executable Language Grounding (XLANG) Lab! We are part of the HKU NLP Group at the University of Hong Kong. We focus on developing grounded AI agents that empower users to use language to interact with digital and physical environments to carry out real-world tasks. Our systems ground language and perception into code and actions executable in the corresponding environments, including databases (data/coding agent), computers (computer use agent), and the physical world (robotic agent) etc,. Through these agents, we aim to enable non-experts to access complex systems such as databases, software, and robots while unlocking functionalities across existing applications and physical systems that dramatically expand AI capabilities.
Welcome to the Executable Language Grounding (XLANG) Lab! We are part of the HKU NLP Group at the University of Hong Kong. We focus on developing grounded AI agents that empower users to use language to interact with digital and physical environments to carry out real-world tasks. Our systems ground language and perception into code and actions executable in the corresponding environments, including databases (data/coding agent), computers (computer use agent), and the physical world (robotic agent) etc,. Through these agents, we aim to enable non-experts to access complex systems such as databases, software, and robots while unlocking functionalities across existing applications and physical systems that dramatically expand AI capabilities.
Welcome to the Executable Language Grounding (XLANG) Lab! We are part of the HKU NLP Group at the University of Hong Kong. We focus on developing grounded AI agents that empower users to use language to interact with digital and physical environments to carry out real-world tasks. Our systems ground language and perception into code and actions executable in the corresponding environments, including databases (data/coding agent), computers (computer use agent), and the physical world (robotic agent) etc,. Through these agents, we aim to enable non-experts to access complex systems such as databases, software, and robots while unlocking functionalities across existing applications and physical systems that dramatically expand AI capabilities.
Welcome to the Executable Language Grounding (XLANG) Lab! We are part of the HKU NLP Group at the University of Hong Kong. We focus on developing grounded AI agents that empower users to use language to interact with digital and physical environments to carry out real-world tasks. Our systems ground language and perception into code and actions executable in the corresponding environments, including databases (data/coding agent), computers (computer use agent), and the physical world (robotic agent) etc,. Through these agents, we aim to enable non-experts to access complex systems such as databases, software, and robots while unlocking functionalities across existing applications and physical systems that dramatically expand AI capabilities.
Welcome to the Executable Language Grounding (XLANG) Lab! We are part of the HKU NLP Group at the University of Hong Kong. We focus on developing grounded AI agents that empower users to use language to interact with digital and physical environments to carry out real-world tasks. Our systems ground language and perception into code and actions executable in the corresponding environments, including databases (data/coding agent), computers (computer use agent), and the physical world (robotic agent) etc,. Through these agents, we aim to enable non-experts to access complex systems such as databases, software, and robots while unlocking functionalities across existing applications and physical systems that dramatically expand AI capabilities.
We thank the following institutions for their funding support: Google Research, Amazon AWS, Salesforce Research, and UGC.
Welcome to the Executable Language Grounding (XLANG) Lab! We are part of the HKU NLP Group at the University of Hong Kong. We focus on developing grounded AI agents that empower users to use language to interact with digital and physical environments to carry out real-world tasks. Our systems ground language and perception into code and actions executable in the corresponding environments, including databases (data/coding agent), computers (computer use agent), and the physical world (robotic agent) etc,. Through these agents, we aim to enable non-experts to access complex systems such as databases, software, and robots while unlocking functionalities across existing applications and physical systems that dramatically expand AI capabilities.
We thank the following institutions for their funding support: Google Research, Amazon AWS, Salesforce Research, and UGC.
Our lab is actively engaged in projects focused on creating language model agents that translate language instructions into executable actions across real-world domains such as databases (data agent), web applications (plugins/web agent), and the physical world (robotic agent) etc. We are currently developing an open-source framework to facilitate the construction and assessment of these agents, starting with XLang Agent demos. In the coming months, we'll open-source essential projects like frameworks, models, methods, and benchmarks, aiming to establish a robust community dedicated to building capable multifunctional agents.
Our lab is actively engaged in projects focused on creating language model agents that translate language instructions into executable actions across real-world domains such as databases (data agent), web applications (plugins/web agent), and the physical world (robotic agent) etc. We are currently developing an open-source framework to facilitate the construction and assessment of these agents, starting with XLang Agent demos. In the coming months, we'll open-source essential projects like frameworks, models, methods, and benchmarks, aiming to establish a robust community dedicated to building capable multifunctional agents.
