[License-review] [2nd Resubmission] ModelGo Attribution License, Version 2.0

[Carlo Piana]

Moming, 

while reviewing the modifications to decide on the approval (actually it should be better to withdraw and resubmit at the end of the discussion) I noticed that the modifications only applied to the MG-by and not to the Open Source version. 

Comparing the two texts, moreover I see that here the liability disclaimer says "to the maximum extent permissible under applicable law, the Licensed Materials are provided on an “as is" and “as available” basis without any representation, warranty, *condition* or term of any kind (whether express, implied, statutory or otherwise)... 

"condition, or term" does not appear in the other license and I think it does not make sense adding it at all, since the license has terms and conditions. 

At least, however, I think you should port the improvements of the Attribution license to the Open Source one, I really don't see why, while sharing like 95% of the provisions, this has not been done to the identical ones here: the rationale applies equally. 

I also object using "Source Code Form" for "preferred form for making modifications, since most evidently the definition includes way more than source code and it is not good practice to define something with a name which is misleading. 

I am still dubious that you can include the Output in the Derivative definition and that a license can purport to control it. This shall undergo more discussion, here and elsewhere, as it is a central point upon which I tried to make an impression every time I discussed porting Open Source concepts to the world of AI. 

At present, I am not inclined to approve the ModelGo Open Source license, while for the Attribution, after the changes at least, I don't see major problems. 

For the "zero", I think the title is misleading, because it has no "zero" conditions, and I have not made a final opinion yet. 

Best, 

Carlo 

> Da: "Moming Duan" <duanmoming at gmail.com>
> A: "license-review at lists.opensource.org" <license-review at lists.opensource.org>
> Inviato: Mercoledì, 18 giugno 2025 11:31:21
> Oggetto: [License-review] [2nd Resubmission] ModelGo Attribution License,
> Version 2.0

> Dear OSI Community,

> Following our previous discussions in May, I have made further revisions to the
> ModelGo Attribution License (MG-BY-2.0). I am submitting this updated version
> for OSI review via this email. The license text is attached.

> —————— Major Updates to Previous Submission

> * Removes restrictions on model output.
> * Revises the termination clause to provide for automatic termination.
> * Adds more explicit granting of rights in Section 2.1.
> * Narrows the definition of “Derivative Materials” by including the phrase: “in
> order to replicate, approximate, or otherwise achieve functional behavior that
> is similar to the Model.”
> * Removes “Derivative Materials” in Section 5: “Nothing in this License permits
> You to modify this License as applied to the Licensed Materials.”
> * Fixes typos and formatting issues.

> —————— License Introduction

> License Name : ModelGo Attribution License
> Version : 2.0
> Short Identifier: MG-BY-2.0
> Copyleft: No
> Legacy or New : New License
> Drafted By Lawyer : Yes, Rajah & Tann Singapore LLP
> Approved or Used by Projects : No

> License URL : [ https://ids.nus.edu.sg/modelgo-mg-by.html |
> https://ids.nus.edu.sg/modelgo-mg-by.html ]
> Introduction and Video : [ https://www.modelgo.li/ | https://www.modelgo.li/ ]

> Overview :

> ModelGo Attribution License Version 2.0 (MG-BY-2.0) is a new license designed
> for publishing models (typically neural networks like Llama2, DeepSeek). It is
> one of the variants in the ModelGo License family. MG-BY-2.0 is the a
> permissive license in the ModelGo family, requiring that the original license
> and attribution be provided when distributing the original Licensed Materials
> or Derivative Materials ( Licensed Materials and Derivative Materials are
> defined in Clause 1). A statement of modification is required, if applicable.
> (Red content represents the differences from MG0-2.0 license)

> Complies with OSD:

> OSD 3 Derived Works — MG-BY-2.0 Clause 2.1 (a) grants copyright and patent
> rights to create derivatives.
> OSD 5 and OSD 6 — No discrimination clause is included in MG-BY-2.0.
> OSD 9 License Must Not Restrict Other Software — No such restriction is included
> in MG-BY-2.0.

> The Gap to Fill:
> Model sharing is very common on the web, with over 1.4 million models currently
> listed on Hugging Face ( [ https://huggingface.co/models |
> https://huggingface.co/models ] ). However, most of these models are not
> properly licensed. When publishing their models, developers typically choose
> from three main options (as seen in the model license tags on the Hugging Face
> website):

>     * OSS licenses, e.g., Apache-2.0, MIT
>    * Open responsible AI licenses (OpenRAILs), e.g., CreativeML-OpenRAIL-M,
>     OpenRAIL++
>     * Proprietary Licenses, e.g., Llama2, Llama3

> However, not all licenses are well-suited for model publishing.

> Why not use OSS licenses?
> Traditional OSS licenses lack clear definitions regarding machine learning
> concepts, such as Models, Output, and Derivatives created through knowledge
> transfer. This ambiguity can result in certain ML activities (e.g.,
> Distillation, Mix-of-Expert) being beyond the control of the model owner.

> Why not use OpenRAILs?
> Recently, Responsible AI Licenses ( [ https://www.licenses.ai/ |
> https://www.licenses.ai/ ] ) have been widely advocated to govern AI
> technologies, aiming to restrict unlawful and unethical uses of models. While I
> acknowledge the growing need for such governance, these copyleft-style
> restrictions do not comply with the OSD and may cause incompatibility with
> licenses like GPL-3.0. Another concern is that these behavioral restrictions
> may proliferate within the AI model ecosystem, increasing the risk of license
> breaches.

> Why not use Llama2 or Llama3 Licenses?
> These licenses are proprietary licenses that are not reusable. Furthermore, they
> include exclusive terms such as "You will not use the Llama Materials or any
> output or results of the Llama Materials to improve any other large language
> model" and copyleft-style behavioral restrictions.

> In fact, the dilemma in current model publishing is the lack of a
> general-purpose license for model developers. Additionally, since no single
> license meets diverse model publishing needs, some developers resort to using
> CC licenses with different elements. However, CC licenses are ill-suited for
> this purpose as they do not grant patent rights. This motivated the drafting of
> ModelGo License family, which provides different licensing elements similar to
> CC but specifically designed for model publishing.

> Comparison with Existing OSI-Approved Licenses:
> Since I could not find an OSI-approved model license, I can only compare
> MG-BY-2.0 with one similar OSS license — Apache-2.0

> * MG-BY-2.0 defines licensed materials and derivative works differently from
> Apache-2.0, tailoring them to models.
> * MG-BY-2.0 can govern the remote access (e.g., chatbot) scenario.

> If further comparisons or supporting evidence are needed to strengthen my
> claims, please let me know. I am more than willing to engage in further
> discussions with the OSI community about this license and contribute to
> promoting standardized model publishing. 🤗

> Best,
> Moming

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