pull openelm

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by Atreyu4EVR - opened
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  1. LICENSE +47 -88
  2. README.md +2 -2
LICENSE CHANGED
@@ -1,88 +1,47 @@
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- Disclaimer: IMPORTANT: This Apple Machine Learning Research Model is
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- specifically developed and released by Apple Inc. ("Apple") for the sole purpose
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- of scientific research of artificial intelligence and machine-learning
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- technology. Apple Machine Learning Research Model” means the model, including
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- but not limited to algorithms, formulas, trained model weights, parameters,
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- configurations, checkpoints, and any related materials (including
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- documentation).
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-
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- This Apple Machine Learning Research Model is provided to You by
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- Apple in consideration of your agreement to the following terms, and your use,
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- modification, creation of Model Derivatives, and or redistribution of the Apple
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- Machine Learning Research Model constitutes acceptance of this Agreement. If You
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- do not agree with these terms, please do not use, modify, create Model
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- Derivatives of, or distribute this Apple Machine Learning Research Model or
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- Model Derivatives.
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-
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- * License Scope: In consideration of your agreement to abide by the following
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- terms, and subject to these terms, Apple hereby grants you a personal,
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- non-exclusive, worldwide, non-transferable, royalty-free, revocable, and
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- limited license, to use, copy, modify, distribute, and create Model
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- Derivatives (defined below) of the Apple Machine Learning Research Model
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- exclusively for Research Purposes. You agree that any Model Derivatives You
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- as well. “Research Purposes” means non-commercial scientific research and
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- academic development activities, such as experimentation, analysis, testing
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- conducted by You with the sole intent to advance scientific knowledge and
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- research. “Research Purposes” does not include any commercial exploitation,
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- product development or use in any commercial product or service.
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-
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- * Distribution of Apple Machine Learning Research Model and Model Derivatives:
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- Machine Learning Research Model is licensed under the Apple Machine Learning
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- Research Model License Agreement.” Additionally, all Model Derivatives must
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- changes made to the Apple Machine Learning Research Model. The name,
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- trademarks, service marks or logos of Apple may not be used to endorse or
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- Derivatives” means any models or any other artifacts created by modifications,
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- improvements, adaptations, alterations to the architecture, algorithm or
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- training processes of the Apple Machine Learning Research Model, or by any
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- retraining, fine-tuning of the Apple Machine Learning Research Model.
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-
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- * No Other License: Except as expressly stated in this notice, no other rights
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- or licenses, express or implied, are granted by Apple herein, including but
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- not limited to any patent, trademark, and similar intellectual property rights
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- the Model Derivatives or by other works in which the Apple Machine Learning
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- Research Model may be incorporated.
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-
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- * Compliance with Laws: Your use of Apple Machine Learning Research Model must
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-
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- * Term and Termination: The term of this Agreement will begin upon your
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- Model and will continue until terminated in accordance with the following
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- survive termination.
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-
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- * Disclaimer and Limitation of Liability: This Apple Machine Learning Research
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- Model and any outputs generated by the Apple Machine Learning Research Model
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- are provided on an “AS IS” basis. APPLE MAKES NO WARRANTIES, EXPRESS OR
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- * Governing Law: This Agreement will be governed by and construed under the laws
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- the Agreement except that the arbitration clause and any arbitration hereunder
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- shall be governed by the Federal Arbitration Act, Chapters 1 and 2. 
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-
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- Copyright (C) 2025 Apple Inc. All Rights Reserved.
 
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+ Copyright (C) 2024 Apple Inc. All Rights Reserved.
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+
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+ Disclaimer: IMPORTANT: This Apple software is supplied to you by Apple
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+ Inc. ("Apple") in consideration of your agreement to the following
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+ terms, and your use, installation, modification or redistribution of
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+ this Apple software constitutes acceptance of these terms. If you do
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+ not agree with these terms, please do not use, install, modify or
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+ redistribute this Apple software.
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+
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+ In consideration of your agreement to abide by the following terms, and
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+ subject to these terms, Apple grants you a personal, non-exclusive
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+ license, under Apple's copyrights in this original Apple software (the
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+ "Apple Software"), to use, reproduce, modify and redistribute the Apple
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+ Software, with or without modifications, in source and/or binary forms;
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+ provided that if you redistribute the Apple Software in its entirety and
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+ without modifications, you must retain this notice and the following
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+ text and disclaimers in all such redistributions of the Apple Software.
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+ Neither the name, trademarks, service marks or logos of Apple Inc. may
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+ be used to endorse or promote products derived from the Apple Software
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+ without specific prior written permission from Apple. Except as
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+ expressly stated in this notice, no other rights or licenses, express or
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+ implied, are granted by Apple herein, including but not limited to any
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+ patent rights that may be infringed by your derivative works or by other
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+ works in which the Apple Software may be incorporated.
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+
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+ The Apple Software is provided by Apple on an "AS IS" basis. APPLE
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+ MAKES NO WARRANTIES, EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION
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+ THE IMPLIED WARRANTIES OF NON-INFRINGEMENT, MERCHANTABILITY AND FITNESS
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+ FOR A PARTICULAR PURPOSE, REGARDING THE APPLE SOFTWARE OR ITS USE AND
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+ OPERATION ALONE OR IN COMBINATION WITH YOUR PRODUCTS.
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+ SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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+ INTERRUPTION) ARISING IN ANY WAY OUT OF THE USE, REPRODUCTION,
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+ MODIFICATION AND/OR DISTRIBUTION OF THE APPLE SOFTWARE, HOWEVER CAUSED
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+ AND WHETHER UNDER THEORY OF CONTRACT, TORT (INCLUDING NEGLIGENCE),
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+ STRICT LIABILITY OR OTHERWISE, EVEN IF APPLE HAS BEEN ADVISED OF THE
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+ POSSIBILITY OF SUCH DAMAGE.
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+
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+
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+ -------------------------------------------------------------------------------
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+ SOFTWARE DISTRIBUTED IN THIS REPOSITORY:
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+
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+ This software includes a number of subcomponents with separate
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+ copyright notices and license terms - please see the file ACKNOWLEDGEMENTS.
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+ -------------------------------------------------------------------------------
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
README.md CHANGED
@@ -1,5 +1,5 @@
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  ---
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- license: apple-amlr
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  license_name: apple-sample-code-license
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  license_link: LICENSE
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  ---
@@ -8,7 +8,7 @@ license_link: LICENSE
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  *Sachin Mehta, Mohammad Hossein Sekhavat, Qingqing Cao, Maxwell Horton, Yanzi Jin, Chenfan Sun, Iman Mirzadeh, Mahyar Najibi, Dmitry Belenko, Peter Zatloukal, Mohammad Rastegari*
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- We introduce **OpenELM**, a family of **Open** **E**fficient **L**anguage **M**odels. OpenELM uses a layer-wise scaling strategy to efficiently allocate parameters within each layer of the transformer model, leading to enhanced accuracy. We pretrained OpenELM models using the [CoreNet](https://github.com/apple/corenet) library. We release both pretrained and instruction tuned models with 270M, 450M, 1.1B and 3B parameters. We release the complete framework, encompassing data preparation, training, fine-tuning, and evaluation procedures, alongside multiple pre-trained checkpoints and training logs, to facilitate open research.
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  Our pre-training dataset contains RefinedWeb, deduplicated PILE, a subset of RedPajama, and a subset of Dolma v1.6, totaling approximately 1.8 trillion tokens. Please check license agreements and terms of these datasets before using them.
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  ---
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+ license: other
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  license_name: apple-sample-code-license
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  license_link: LICENSE
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  ---
 
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  *Sachin Mehta, Mohammad Hossein Sekhavat, Qingqing Cao, Maxwell Horton, Yanzi Jin, Chenfan Sun, Iman Mirzadeh, Mahyar Najibi, Dmitry Belenko, Peter Zatloukal, Mohammad Rastegari*
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+ We introduce **OpenELM**, a family of **Open** **E**fficient **L**anguage **M**odels. OpenELM uses a layer-wise scaling strategy to efficiently allocate parameters within each layer of the transformer model, leading to enhanced accuracy. We pretrained OpenELM models using the [CoreNet](https://github.com/apple/corenet) library. We release both pretrained and instruction tuned models with 270M, 450M, 1.1B and 3B parameters.
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  Our pre-training dataset contains RefinedWeb, deduplicated PILE, a subset of RedPajama, and a subset of Dolma v1.6, totaling approximately 1.8 trillion tokens. Please check license agreements and terms of these datasets before using them.
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