All things prompt engineeringpromptbase promptbase is an evolving collection of resources, best practices, and example scripts for eliciting the best performance from foundation models like GPT-4. We currently host scripts demonstrating the Medprompt methodology, including examples of how we further extended this collection of prompting techniques ("Medprompt+") into non-medical domains: Benchmark GPT-4 Prompt GPT-4 Results Gemini Ultra Results MMLU Medprompt+ 90.10% 90.04% GSM…
Simplifying LLM ops in production BricksLLM: AI Gateway For Putting LLM In Production BricksLLM is a cloud native AI gateway written in Go. Currently, it serves as a proxy to OpenAI. We let you create API keys that have rate limits, cost limits and TTLs. The API keys can be used in both development and production to achieve fine-grained access control that is not provided by OpenAI at the moment. The proxy is compatible with OpenAI API and its SDKs. The vision of BricksLLM i…
LLMs as Copilots for Theorem Proving in LeanLean Copilot: LLMs as Copilots for Theorem Proving in Lean Lean Copilot allows large language models (LLMs) to be used in Lean for proof automation, e.g., suggesting tactics/premises and searching for proofs. You can use our built-in models from LeanDojo or bring your own models that run either locally (w/ or w/o GPUs) or on the cloud. Lean.Copilot.demo.mp4 Table of Contents Requirements Using Lean Copilot in Your…
Unofficial Implementation of Animate AnyoneUnofficial Implementation of Animate Anyone Overview This repository contains an simple and unofficial implementation of Animate Anyone. This project is built upon magic-animate and AnimateDiff. Note !!! This project is under continuous development in part-time, there may be bugs in the code, welcome to correct them, I will optimize the code after the pre-trained model is released! Requirements Same as magic-animate. ToDo Release Training Code. Deep…
A toolkit for inference and evaluation of 'mixtral-8x7b-32kseqlen' from Mistral AI MixtralKit A Toolkit for Mixtral Model 📊Performance • ✨Resources • 📖Architecture • 📂Weights • 🔨 Install • 🚀Inference • 🤝 Acknowledgement English | 简体中文 Important 📢 Welcome to try OpenCompass for model evaluation 📢 🤗 Request for update your mixtral-related projects is open! 🙏 This repo is an **experimental** implementation of inference code. 📊 Performance Comparison with Other Models …
2023HW漏洞整理，收集整理漏洞EXp/POC,大部分漏洞来源网络，目前收集整理了100多个poc/exp漏洞收集 2023HW漏洞整理，收集整理漏洞EXp/POC,大部分漏洞来源网络，目前收集整理了100多个poc/exp，善用CTRL+F搜索 2023.12.11 新增漏洞 Apache Struts2 CVE-2023-50164 蓝凌EKP前台授权绕过导致文件上传 通达OA header身份认证绕过漏洞 2023.12.08 新增漏洞 Dedecms v5.7.111前台tags.php SQL注入漏洞 云时空社会化商业ERP任意文件上传 奥威亚视频云平台VideoCover.aspx接口存在任意文件上传漏洞 2023.12.07 新增漏洞 WeiPHP>=5.0 SQL注入漏洞 Apache Ofbiz XML-RPC RCE漏洞-CVE-2023-49070 多个防火墙产品RCE 金蝶Apusic应用服务器任意文件上传 2023.12.05 新增漏洞 速达软件全系产品存在任意文件上传漏洞 易思智能物流无人值守系统5.0存在任意文件上传漏洞 RuoYi…
All the projects related to LlamaLlama Welcome to my Repo! :smile: This repository contains notebooks: That can be run on Google Colab to understand how to use Llama 2 models Examples of fine-tuning Llama 2 models with different datasets (you can) Prompt-engineering with open source tools/frameworks such as Langchain, FAISS, etc and other fun stuff you can do with Llama!
library supporting NLP and CV research on scientific paperspapermage Setup conda create -n papermage python=3.9 conda activate papermage pip install -e '.[dev,predictors,visualizers]' If you're on MacOSX, you'll also want to run: conda install poppler Unit testing python -m pytest for latest failed test python -m pytest --lf --no-cov -n0 for specific test name of class name python -m pytest -k 'TestPDFPlumberParser' --no-cov -n0 Quick start 1. Create a Document for the …
Providing enterprise-grade LLM-based development framework, tools, and fine-tuned models.llmware llmware is a unified, open, extensible framework for LLM-based application patterns including Retrieval Augmented Generation (RAG). This project provides a comprehensive set of tools that anyone can use – from beginner to the most sophisticated AI developer – to rapidly build industrial-grade enterprise LLM-based applications. Key differentiators include: source citation for Q & A scenarios, …