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Author: root <root@hub.scroll.pub> Date: 2024-12-28 18:36:47 +0000 Subject: Initial commit diff --git a/body.html b/body.html new file mode 100644 index 0000000..1b6045e --- /dev/null +++ b/body.html @@ -0,0 +1,29 @@ +<header> + <h1>Running Big LLMs on RISC-V Microcontroller Breakthrough</h1> + <p>Imaginary Research Paper by [Your Name]</p> +</header> +<main> + <section id="abstract"> + <h2>Abstract</h2> + <p>This paper explores the groundbreaking possibility of running large language models (LLMs) on RISC-V microcontrollers, challenging the conventional wisdom that such tasks require high-performance computing resources.</p> + </section> + <section id="introduction"> + <h2>Introduction</h2> + <p>With the rise of edge computing and the need for efficient, low-power devices, the ability to run complex AI models on microcontrollers has become increasingly important. This research demonstrates a novel approach to achieving this goal.</p> + </section> + <section id="methodology"> + <h2>Methodology</h2> + <p>We developed a custom optimization pipeline that reduces the computational and memory requirements of LLMs, making them suitable for RISC-V microcontrollers without significant loss in performance.</p> + </section> + <section id="results"> + <h2>Results</h2> + <p>Our experiments show that it is indeed possible to run LLMs on RISC-V microcontrollers with acceptable latency and accuracy, opening up new possibilities for AI applications in resource-constrained environments.</p> + </section> + <section id="conclusion"> + <h2>Conclusion</h2> + <p>This breakthrough has the potential to revolutionize the field of edge AI, enabling a new generation of smart devices that can perform complex language tasks without relying on cloud computing.</p> + </section> +</main> +<footer> + <p>Contact: [Your Email]</p> +</footer> \ No newline at end of file diff --git a/index.scroll b/index.scroll new file mode 100644 index 0000000..18bc3c6 --- /dev/null +++ b/index.scroll @@ -0,0 +1,8 @@ +buildHtml +baseUrl https://riscv-llm.scroll.pub +metaTags +editButton /edit.html +title Running Big LLMs on RISC-V Microcontroller Breakthrough +style.css +body.html +script.js \ No newline at end of file diff --git a/prompt.json b/prompt.json new file mode 100644 index 0000000..5167f40 --- /dev/null +++ b/prompt.json @@ -0,0 +1,25 @@ +{ + "id": "0d33d3bd-f273-4c13-96b9-e22ead3341e2", + "object": "chat.completion", + "created": 1735410996, + "model": "deepseek-chat", + "choices": [ + { + "index": 0, + "message": { + "role": "assistant", + "content": "---domain---\nriscv-llm.scroll.pub\n---index.scroll---\nbuildHtml\nbaseUrl https://riscv-llm.scroll.pub\nmetaTags\neditButton /edit.html\ntitle Running Big LLMs on RISC-V Microcontroller Breakthrough\nstyle.css\nbody.html\nscript.js\n---body.html---\n<header>\n <h1>Running Big LLMs on RISC-V Microcontroller Breakthrough</h1>\n <p>Imaginary Research Paper by [Your Name]</p>\n</header>\n<main>\n <section id=\"abstract\">\n <h2>Abstract</h2>\n <p>This paper explores the groundbreaking possibility of running large language models (LLMs) on RISC-V microcontrollers, challenging the conventional wisdom that such tasks require high-performance computing resources.</p>\n </section>\n <section id=\"introduction\">\n <h2>Introduction</h2>\n <p>With the rise of edge computing and the need for efficient, low-power devices, the ability to run complex AI models on microcontrollers has become increasingly important. 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