Papirfly delivers enterprise-ready software that transforms how global brands manage and create marketing content. Through advanced Digital Asset Management (DAM) and templated content creation capabilities, Papirfly enables teams to organize, control, and activate assets securely—across every format and region.
Powering over 1 million users in 1,500+ leading organizations, including Mercedes-Benz, Mondelez, and Goldman Sachs, Papirfly helps brands scale creativity without losing control.
Built on a modular SaaS framework, it connects asset storage, brand governance, and content production in one intuitive ecosystem. As part of the Papirfly Group—with Keepeek, Brandpad, and Adgistics—Papirfly continues to innovate for marketing teams that demand efficiency, consistency, and global brand excellence.
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Brandwatch is a leading Social Media Management and Consumer Intelligence solution that empowers over 5,000 of the world's most admired companies to understand and engage with customers at the speed of social. Brandwatch offers one of the most unified social media management platforms around. You can discover, attract and engage with customers, and connect social data to what you already know, across departments and channels. You will love the easy-to-use interface, backed by our dedication to stellar support. Its Consumer Intelligence solution offers AI-enriched data from over 100m social and online sources helping data-driven organizations better understand how consumers feel about their brands, products and industry trends and topics.
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Alpaca
Instruction-following models like GPT-3.5 (text-DaVinci-003), ChatGPT, Claude, and Bing Chat have seen significant advancements in their capabilities, leading to a rise in their usage among individuals in both personal and professional contexts. Despite their growing popularity and integration into daily tasks, these models are not without their shortcomings, as they can sometimes disseminate inaccurate information, reinforce harmful stereotypes, and use inappropriate language. To effectively tackle these critical issues, it is essential for researchers and scholars to become actively involved in exploring these models further. However, conducting research on instruction-following models within academic settings has posed challenges due to the unavailability of models with comparable functionality to proprietary options like OpenAI’s text-DaVinci-003. In response to this gap, we are presenting our insights on an instruction-following language model named Alpaca, which has been fine-tuned from Meta’s LLaMA 7B model, aiming to contribute to the discourse and development in this field. This initiative represents a step towards enhancing the understanding and capabilities of instruction-following models in a more accessible manner for researchers.
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Falcon-40B
Falcon-40B is a causal decoder-only model consisting of 40 billion parameters, developed by TII and trained on 1 trillion tokens from RefinedWeb, supplemented with carefully selected datasets. It is distributed under the Apache 2.0 license.
Why should you consider using Falcon-40B?
This model stands out as the leading open-source option available, surpassing competitors like LLaMA, StableLM, RedPajama, and MPT, as evidenced by its ranking on the OpenLLM Leaderboard.
Its design is specifically tailored for efficient inference, incorporating features such as FlashAttention and multiquery capabilities.
Moreover, it is offered under a flexible Apache 2.0 license, permitting commercial applications without incurring royalties or facing restrictions.
It's important to note that this is a raw, pretrained model and is generally recommended to be fine-tuned for optimal performance in most applications. If you need a version that is more adept at handling general instructions in a conversational format, you might want to explore Falcon-40B-Instruct as a potential alternative.
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