Third Party Software Licenses

The AI profile of Hellobot service includes the following components. Please note that all of the below listed terms are only displayed to comply with the notice requirements of such used components, and such terms in no way apply to the AI profile or any other product or service of Hellobot (including but not limited to the App and the Services).

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Stable Diffusion XL (https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/blob/main/LICENSE.md)

This work has been generated using 'Stable Diffusion XL', a model developed and provided by Stability AI (copyright (c) 2023 Stability AI CreativeML Open RAIL++-M License dated July 26, 2023). The model is used under the CreativeML Open RAIL++-M License, dated July 26, 2023 (attached hereto as below, hereinafter the “License”). This work and the use of this work by you are also governed by the use-based restrictions and other terms set forth in the License.

This model has been fine-tuned from its original version.

Copyright (c) 2023 Stability AI CreativeML Open RAIL++-M License dated July 26, 2023

Section I: PREAMBLE

Multimodal generative models are being widely adopted and used, and have the potential to transform the way artists, among other individuals, conceive and benefit from AI or ML technologies as a tool for content creation.

Notwithstanding the current and potential benefits that these artifacts can bring to society at large, there are also concerns about potential misuses of them, either due to their technical limitations or ethical considerations.

In short, this license strives for both the open and responsible downstream use of the accompanying model. When it comes to the open character, we took inspiration from open source permissive licenses regarding the grant of IP rights. Referring to the downstream responsible use, we added use-based restrictions not permitting the use of the model in very specific scenarios, in order for the licensor to be able to enforce the license in case potential misuses of the Model may occur. At the same time, we strive to promote open and responsible research on generative models for art and content generation.

Even though downstream derivative versions of the model could be released under different licensing terms, the latter will always have to include - at minimum - the same use-based restrictions as the ones in the original license (this license). We believe in the intersection between open and responsible AI development; thus, this agreement aims to strike a balance between both in order to enable responsible open-science in the field of AI.

This CreativeML Open RAIL++-M License governs the use of the model (and its derivatives) and is informed by the model card associated with the model.

NOW THEREFORE, You and Licensor agree as follows:

  1. Definitions

"License" means the terms and conditions for use, reproduction, and Distribution as defined in this document.

"Data" means a collection of information and/or content extracted from the dataset used with the Model, including to train, pretrain, or otherwise evaluate the Model. The Data is not licensed under this License.

"Output" means the results of operating a Model as embodied in informational content resulting therefrom.

"Model" means any accompanying machine-learning based assemblies (including checkpoints), consisting of learnt weights, parameters (including optimizer states), corresponding to the model architecture as embodied in the Complementary Material, that have been trained or tuned, in whole or in part on the Data, using the Complementary Material.

"Derivatives of the Model" means all modifications to the Model, works based on the Model, or any other model which is created or initialized by transfer of patterns of the weights, parameters, activations or output of the Model, to the other model, in order to cause the other model to perform similarly to the Model, including - but not limited to - distillation methods entailing the use of intermediate data representations or methods based on the generation of synthetic data by the Model for training the other model.