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llamafile (Apache 2.0)
Copyright 2023 Mozilla Foundation
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Cosmopolitan
Copyright 2024 Justine Alexandra Roberts Tunney
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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
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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)
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Smoothsort (MIT License)
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Optimized Routines (MIT License)
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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,
creating, or distributing child exploitative content or Child
Sexual Abuse Material.
Sensitive information: collecting, disclosing, or inferring
health, demographic, or other sensitive personal or private
information about individuals without lawful authority or
obtaining all rights and consents required by applicable laws.
Fraud and deception: misrepresenting generated content from models
as human-created or allowing individuals to create false
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
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