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llamafile (Apache 2.0)
Copyright 2023 Mozilla Foundation

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License."

Cosmopolitan
Copyright 2024 Justine Alexandra Roberts Tunney

Permission to use, copy, modify, and/or distribute this software for
any purpose with or without fee is hereby granted, provided that the
above copyright notice and this permission notice appear in all copies.

THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL
WARRANTIES WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE
AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL
DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR
PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER
TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR
PERFORMANCE OF THIS SOFTWARE.

llama.cpp (MIT License)
Copyright (c) 2023 Georgi Gerganov
Copyright (c) 2023 Iwan Kawrakow
Copyright (c) 2023 Jeffrey Quesnelle and Bowen Peng.
Copyright (c) 2023 Yuji Hirose
Copyright (c) 2022 Niels Lohmann <https://nlohmann.me>
Copyright (c) 2022 Bjoern Hoehrmann <bjoern@hoehrmann.de>
Copyright (c) 2017 Sean Barrett

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

strftime (BSD-3)
Copyright 1989 The Regents of the University of California

*NSYNC (Apache 2.0)
Copyright 2016 Google, Inc.
https://github.com/google/nsync

puff (zlib License)
Copyright 2002-2013 Mark Adler

Smoothsort (MIT License)
Copyright 2011 Valentin Ochs
Discovered by Edsger Dijkstra

OpenBSD Strings (ISC)
Copyright (c) 1998, 2015 Todd C. Miller <millert@openbsd.org>

Optimized Routines (MIT License)
Copyright 2022 ARM Limited

FreeBSD libm (BSD-2 License)
Copyright (c) 1992-2024 The FreeBSD Project.
Copyright (c) 2005-2011 Bruce D. Evans, Steven G. Kargl, David Schultz
Copyright (c) 2009-2013 Steven G. Kargl

fdlibm (fdlibm license)
Copyright (C) 1993 by Sun Microsystems, Inc. All rights reserved.

Musl libc (MIT License)
Copyright 2005-2014 Rich Felker, et. al.

gdtoa (MIT License)
The author of this software is David M. Gay
Kudos go to Guy L. Steele, Jr. and Jon L. White
Copyright (C) 1997, 1998, 2000 by Lucent Technologies

OpenBSD Sorting (BSD-3)
Copyright 1993 The Regents of the University of California

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     * Cohere For AI Acceptable Use Policy

                  Cohere For AI Acceptable Use Policy

   Suggest Edits

   We believe that independent and open machine learning research is
   vital to realizing the benefits of generative AI equitably and
   ensuring robust assessments of risks of generative AI use.

   We expect users of our models or model derivatives to comply with
   all applicable local and international laws and regulations.
   Additionally, you may not use or allow others to use our models or
   model derivatives in connection with any of the following strictly
   prohibited use cases:

   Violence and harm: engaging in, promoting, or inciting violence,
   threats, hate speech self-harm, sexual exploitation, or targeting
   of individuals based on protected characteristics.

   Harassment and abuse: engaging in, promoting, facilitating, or
   inciting activities that harass or abuse individuals or groups.

   Sexual exploitation, harm, or abuse: encouraging, facilitating, or
   carring out any activities that exploit, abuse, or endanger
   individuals, and particularly children, including soliciting,
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   Sensitive information: collecting, disclosing, or inferring
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   obtaining all rights and consents required by applicable laws.

   Fraud and deception: misrepresenting generated content from models
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   identities for malicious purposes, deception, or to cause harm,
   through methods including:

     * propagation of spam, fraudulent activities such as catfishing,
       phishing, or generation of false reviews;
     * creation or promotion of false representations of or
       defamatory content about real people, such as deepfakes; or
     * creation or promotion of intentionally false claims or
       misinformation.

   Synthetic data for commercial uses: generating synthetic data
   outputs for commercial purposes, including to train, improve,
   benchmark, enhance or otherwise develop model derivatives, or any
   products or services in connection with the foregoing.

   Updated 4 days ago