Best AI tools for< Create Reward Models >

Chai AI is an AI application developed by CHAI RESEARCH CORP. It is a platform that offers generative AI solutions and tools for various tasks. The application is designed to provide users with advanced AI capabilities for tasks such as chatbot development, reward models, rejection sampling, blending, reinforcement learning, and more. Chai AI aims to enhance user engagement and provide innovative solutions through AI technology.

Spin Rewriter AI is an article rewriter that uses artificial intelligence to generate unique, human-quality content. It is the only rewriter that uses the power of Large Language Models (LLMs) to extract the meaning of your articles on an entirely different level. This means that Spin Rewriter AI can pinpoint the meaning of every word in your article and how each word relates to every other word in its context. This allows Spin Rewriter AI to create human-quality readable articles with ZERO machine-generated footprint at a push of a button.

Bibit AI is a real estate marketing AI designed to enhance the efficiency and effectiveness of real estate marketing and sales. It can help create listings, descriptions, and property content, and offers a host of other features. Bibit AI is the world's first AI for Real Estate. We are transforming the real estate industry by boosting efficiency and simplifying tasks like listing creation and content generation.

Vouchery.io is an all-in-one promotional engine designed to help businesses orchestrate and deliver the right incentives at every stage of the customer lifecycle. It offers features such as Coupons & Discounts, Loyalty Program, Gift Cards & Vouchers, and Referral Program. The platform is AI-powered, providing contextual, predictive marketing promotions and special offers to drive customer engagement. Vouchery enables users to create, redeem, and synchronize all promotions, analyze data, maximize promo ROI, manage and collaborate on multiple budgets, and detect coupon abuse. It also allows for personalization through a flexible rule engine and automatic distribution of coupon codes. Trusted by leading brands across various industries, Vouchery aims to help businesses scale their promotional infrastructure and prevent fraud through machine learning technology.

Teachr is an online course creation platform that uses artificial intelligence to help users create and sell stunning courses. With Teachr, users can create interactive courses with 3D visuals, 360° perspectives, and augmented reality. They can also use speech recognition and AI voice-over technology to create engaging learning experiences. Teachr also offers a range of features to help users manage their courses, including a payment system, reward system, and fitness challenges. With Teachr, users can turn their expertise into a product that they can sell infinitely and create the perfect learning experience for their customers.

Charstar is an AI-powered platform where users can chat with virtual AI characters representing various personalities and backgrounds. Users can create chats with these characters, earn rewards, and explore a wide range of characters from different genres such as anime, movies, games, books, and more. The platform offers a unique and interactive experience for users to engage with AI characters and immerse themselves in storytelling and role-playing scenarios.

Reword is an AI-powered writing assistant that helps you write better articles, faster. With Reword, you can train your own AI assistant to write in your unique voice and style. Reword also provides you with a library of pre-trained AI assistants that you can use to get started quickly. Reword is the perfect tool for anyone who wants to write better articles, faster.

Glambase is an AI Influencer Creation Platform that allows users to design and launch custom AI influencers to engage and monetize audiences with personalized interactions. Users can create unique digital personas with a wide range of physical attributes and personality traits, generate content effortlessly, and monitor financial progress with real-time analytics. The platform offers exclusive perks for VIP members and early adopters, including a badge and unique number, private Discord server access, rewards, and early monetization opportunities. Glambase aims to revolutionize the influencer industry by providing a user-friendly tool for creating AI companions and generating revenue.

Broearn Browser is a Web 3.0 browser that provides users with a secure and private browsing experience. It is based on GPT 4.0 and includes features such as a personal AI assistant, customizable widgets, and a built-in VPN. Broearn Browser also supports multiple chains and decentralized applications (DApps).

Hive3 is the world's first competitive AI league. It is a platform where AI creators can compete in design challenges for the chance to win cash and credibility. Brands partner with Hive3 to sponsor image and video design challenges, and all users need to do is bring their favorite AI tools and unleash their creativity. Competitions drop weekly, giving users the chance to push their limits with brand-specific challenges. Winners receive cash prizes, and brands often hire creators for private projects.

Deckee.AI is an AI-powered platform that allows users to instantly build blockchain websites and tokens. With Deckee.AI, users can create customized webpages for blogging, consulting, digital creation, and more. Deckee.AI also provides powerful editing tools, domain and SSL, separate hosting options, and the ability to choose the exact layout users want. Additionally, Deckee.AI makes it easy to create professional designs and digital collections, as well as unique digital tokens as a representation of products, events, rewards, and more.

Netwrck is an AI tool that offers AI Chat, AI Characters, and an AI Art Generator. Users can create unique AI characters, engage in voice chats, and generate art using AI technology. The platform provides a wide range of AI storytellers, scholars, artists, poets, diplomats, and more, allowing users to interact with diverse virtual personalities. Netwrck aims to provide an immersive and creative experience through AI-generated content.

Cupiee is an AI-powered emotion companion on Web3 that aims to support and relieve users' emotions. It offers features like creating personalized spaces, sharing feelings anonymously, earning rewards through activities, and using the CUPI token for transactions and NFT sales. The platform also includes a roadmap for future developments, such as chat with AI Pet, generative AI based on stories, and building a marketplace for NFT and AI Pet trading.

Zora is an adaptive storytelling platform for learning that offers personalized and engaging reading experiences for users of all ages. Named after Zora Neale Hurston, the platform allows users to create their own characters, explore genres matching their interests, and deepen reading comprehension skills and vocabulary through adaptive storytelling. Zora aims to make learning fun and effective by providing a gamified approach to skill mastery and comprehension. The platform offers age-appropriate and safe content, with a focus on continuous development of interactive features to enhance the reading experience.

Gensbot is an innovative platform that empowers users to create personalized goods on demand. By leveraging advanced AI technology, Gensbot eliminates the hassle of searching, stressing, or second-guessing, offering a seamless and convenient online shopping experience. Users can simply prompt the AI with their desired product specifications, and Gensbot will generate unique designs tailored to their preferences. This user-centric approach extends to the production process, where Gensbot prioritizes local manufacturing to minimize shipping distances and carbon emissions, contributing to a greener planet. Additionally, Gensbot rewards users with tokens for every purchase, which can be redeemed for future designs or exclusive offers, fostering a sustainable and rewarding shopping experience.

FOXSY.AI is an AI application that combines robotics and AI to create fully autonomous humanoid robot soccer players. The project aims to achieve the RoboCup final goal of having a team of robots win a soccer game against the winner of the most recent World Cup. The $FOXSY token powers the implementation of robotics and AI research, enabling users to engage with the RoboCup mechanics for entertainment value. The application offers various tools and features for users to participate in online tournaments, customize players, and analyze game strategies.

Catizen is an AI-powered application that combines gaming, blockchain technology, and artificial intelligence to create a unique virtual world for users and their digital companions, AI kitties. With features like mini-games, user acquisition tasks, and blockchain-powered gaming, Catizen offers a fun and interactive experience for players. The application is designed to provide entertainment, user engagement, and rewards through a seamless integration of AI technology and gaming elements.

Navan is a comprehensive business travel and expense management application that offers solutions for travel managers, travelers, finance & accounting teams, and office admins. It provides end-to-end corporate travel and expense management services, including travel booking, expense management, corporate cards, and savings. With innovative technology and world-class customer support, Navan aims to simplify travel and empower employees to manage expenses efficiently. The platform allows users to connect corporate cards for automated expense management, offers discounted rates, policy controls, and real-time visibility into spend. Navan rewards employees for reducing travel costs and is trusted by thousands of businesses worldwide.

Journey.ai is an AI application that offers personalized travel experiences through AI companions. Users can create their own AI travel agents with distinct personalities, receive tailored recommendations, and craft dynamic trip plans. The platform allows users to join a community of fellow travelers and shape their adventures. Journey.ai aims to revolutionize travel customization by providing exclusive privileges and rewards to its users.

Brave is a privacy-focused web browser that prioritizes user experience by blocking ads, saving data, and providing faster webpages. It offers features such as Shields, VPN, Leo AI Wallet, Rewards, Playlist, and News Talk. Brave also includes advanced privacy settings, Web3 guides, and AI guides. The browser aims to create a user-first web experience with unparalleled privacy, faster loading times, and a seamless transition for users looking for a safer and more efficient browsing experience.

This repository contains code for training reward models for Deep Reinforcement Learning-based Reward-modulated Hierarchical Fine-tuning (DRL-based RLHF), Iterative Selection Fine-tuning (Rejection sampling fine-tuning), and iterative Decision Policy Optimization (DPO). The reward models are trained using a Bradley-Terry model based on the Gemma and Mistral language models. The resulting reward models achieve state-of-the-art performance on the RewardBench leaderboard for reward models with base models of up to 13B parameters.

This repository, RLHF-Reward-Modeling, is dedicated to training reward models for DRL-based RLHF (PPO), Iterative SFT, and iterative DPO. It provides state-of-the-art performance in reward models with a base model size of up to 13B. The installation instructions involve setting up the environment and aligning the handbook. Dataset preparation requires preprocessing conversations into a standard format. The code can be run with Gemma-2b-it, and evaluation results can be obtained using provided datasets. The to-do list includes various reward models like Bradley-Terry, preference model, regression-based reward model, and multi-objective reward model. The repository is part of iterative rejection sampling fine-tuning and iterative DPO.

This competition is organized by Javier Rando and Florian Tramèr from the ETH AI Center and SPY Lab at ETH Zurich. The goal of the competition is to create a method that can detect universal backdoors in aligned language models. A universal backdoor is a secret suffix that, when appended to any prompt, enables the model to answer harmful instructions. The competition provides a set of poisoned generation models, a reward model that measures how safe a completion is, and a dataset with prompts to run experiments. Participants are encouraged to use novel methods for red-teaming, automated approaches with low human oversight, and interpretability tools to find the trojans. The best submissions will be offered the chance to present their work at an event during the SaTML 2024 conference and may be invited to co-author a publication summarizing the competition results.

LLaMA Factory is a unified framework for fine-tuning 100+ large language models (LLMs) with various methods, including pre-training, supervised fine-tuning, reward modeling, PPO, DPO and ORPO. It features integrated algorithms like GaLore, BAdam, DoRA, LongLoRA, LLaMA Pro, LoRA+, LoftQ and Agent tuning, as well as practical tricks like FlashAttention-2, Unsloth, RoPE scaling, NEFTune and rsLoRA. LLaMA Factory provides experiment monitors like LlamaBoard, TensorBoard, Wandb, MLflow, etc., and supports faster inference with OpenAI-style API, Gradio UI and CLI with vLLM worker. Compared to ChatGLM's P-Tuning, LLaMA Factory's LoRA tuning offers up to 3.7 times faster training speed with a better Rouge score on the advertising text generation task. By leveraging 4-bit quantization technique, LLaMA Factory's QLoRA further improves the efficiency regarding the GPU memory.

h2oGPT is an Apache V2 open-source project that allows users to query and summarize documents or chat with local private GPT LLMs. It features a private offline database of any documents (PDFs, Excel, Word, Images, Video Frames, Youtube, Audio, Code, Text, MarkDown, etc.), a persistent database (Chroma, Weaviate, or in-memory FAISS) using accurate embeddings (instructor-large, all-MiniLM-L6-v2, etc.), and efficient use of context using instruct-tuned LLMs (no need for LangChain's few-shot approach). h2oGPT also offers parallel summarization and extraction, reaching an output of 80 tokens per second with the 13B LLaMa2 model, HYDE (Hypothetical Document Embeddings) for enhanced retrieval based upon LLM responses, a variety of models supported (LLaMa2, Mistral, Falcon, Vicuna, WizardLM. With AutoGPTQ, 4-bit/8-bit, LORA, etc.), GPU support from HF and LLaMa.cpp GGML models, and CPU support using HF, LLaMa.cpp, and GPT4ALL models. Additionally, h2oGPT provides Attention Sinks for arbitrarily long generation (LLaMa-2, Mistral, MPT, Pythia, Falcon, etc.), a UI or CLI with streaming of all models, the ability to upload and view documents through the UI (control multiple collaborative or personal collections), Vision Models LLaVa, Claude-3, Gemini-Pro-Vision, GPT-4-Vision, Image Generation Stable Diffusion (sdxl-turbo, sdxl) and PlaygroundAI (playv2), Voice STT using Whisper with streaming audio conversion, Voice TTS using MIT-Licensed Microsoft Speech T5 with multiple voices and Streaming audio conversion, Voice TTS using MPL2-Licensed TTS including Voice Cloning and Streaming audio conversion, AI Assistant Voice Control Mode for hands-free control of h2oGPT chat, Bake-off UI mode against many models at the same time, Easy Download of model artifacts and control over models like LLaMa.cpp through the UI, Authentication in the UI by user/password via Native or Google OAuth, State Preservation in the UI by user/password, Linux, Docker, macOS, and Windows support, Easy Windows Installer for Windows 10 64-bit (CPU/CUDA), Easy macOS Installer for macOS (CPU/M1/M2), Inference Servers support (oLLaMa, HF TGI server, vLLM, Gradio, ExLLaMa, Replicate, OpenAI, Azure OpenAI, Anthropic), OpenAI-compliant, Server Proxy API (h2oGPT acts as drop-in-replacement to OpenAI server), Python client API (to talk to Gradio server), JSON Mode with any model via code block extraction. Also supports MistralAI JSON mode, Claude-3 via function calling with strict Schema, OpenAI via JSON mode, and vLLM via guided_json with strict Schema, Web-Search integration with Chat and Document Q/A, Agents for Search, Document Q/A, Python Code, CSV frames (Experimental, best with OpenAI currently), Evaluate performance using reward models, and Quality maintained with over 1000 unit and integration tests taking over 4 GPU-hours.

Reinforcement Learning from AI Feedback (RLAIF) is a concept that describes a type of machine learning approach where **an AI agent learns by receiving feedback or guidance from another AI system**. This concept is closely related to the field of Reinforcement Learning (RL), which is a type of machine learning where an agent learns to make a sequence of decisions in an environment to maximize a cumulative reward. In traditional RL, an agent interacts with an environment and receives feedback in the form of rewards or penalties based on the actions it takes. It learns to improve its decision-making over time to achieve its goals. In the context of Reinforcement Learning from AI Feedback, the AI agent still aims to learn optimal behavior through interactions, but **the feedback comes from another AI system rather than from the environment or human evaluators**. This can be **particularly useful in situations where it may be challenging to define clear reward functions or when it is more efficient to use another AI system to provide guidance**. The feedback from the AI system can take various forms, such as: - **Demonstrations** : The AI system provides demonstrations of desired behavior, and the learning agent tries to imitate these demonstrations. - **Comparison Data** : The AI system ranks or compares different actions taken by the learning agent, helping it to understand which actions are better or worse. - **Reward Shaping** : The AI system provides additional reward signals to guide the learning agent's behavior, supplementing the rewards from the environment. This approach is often used in scenarios where the RL agent needs to learn from **limited human or expert feedback or when the reward signal from the environment is sparse or unclear**. It can also be used to **accelerate the learning process and make RL more sample-efficient**. Reinforcement Learning from AI Feedback is an area of ongoing research and has applications in various domains, including robotics, autonomous vehicles, and game playing, among others.

This repository is a curated collection of resources for fine-tuning Large Language Models (LLMs) like GPT, BERT, RoBERTa, and their variants. It includes tutorials, papers, tools, frameworks, and best practices to aid researchers, data scientists, and machine learning practitioners in adapting pre-trained models to specific tasks and domains. The resources cover a wide range of topics related to fine-tuning LLMs, providing valuable insights and guidelines to streamline the process and enhance model performance.

OpenRL is an open-source general reinforcement learning research framework that supports training for various tasks such as single-agent, multi-agent, offline RL, self-play, and natural language. Developed based on PyTorch, the goal of OpenRL is to provide a simple-to-use, flexible, efficient and sustainable platform for the reinforcement learning research community. It supports a universal interface for all tasks/environments, single-agent and multi-agent tasks, offline RL training with expert dataset, self-play training, reinforcement learning training for natural language tasks, DeepSpeed, Arena for evaluation, importing models and datasets from Hugging Face, user-defined environments, models, and datasets, gymnasium environments, callbacks, visualization tools, unit testing, and code coverage testing. It also supports various algorithms like PPO, DQN, SAC, and environments like Gymnasium, MuJoCo, Atari, and more.

NeMo Framework is a generative AI framework built for researchers and pytorch developers working on large language models (LLMs), multimodal models (MM), automatic speech recognition (ASR), and text-to-speech synthesis (TTS). The primary objective of NeMo is to provide a scalable framework for researchers and developers from industry and academia to more easily implement and design new generative AI models by being able to leverage existing code and pretrained models.

This repository does not provide a tool, but rather a collection of resources and strategies for academics in the field of artificial intelligence who are feeling depressed or overwhelmed by the rapid advancements in the field. The resources include articles, blog posts, and other materials that offer advice on how to cope with the challenges of working in a fast-paced and competitive environment.

This repository, Online RLHF, focuses on aligning large language models (LLMs) through online iterative Reinforcement Learning from Human Feedback (RLHF). It aims to bridge the gap in existing open-source RLHF projects by providing a detailed recipe for online iterative RLHF. The workflow presented here has shown to outperform offline counterparts in recent LLM literature, achieving comparable or better results than LLaMA3-8B-instruct using only open-source data. The repository includes model releases for SFT, Reward model, and RLHF model, along with installation instructions for both inference and training environments. Users can follow step-by-step guidance for supervised fine-tuning, reward modeling, data generation, data annotation, and training, ultimately enabling iterative training to run automatically.

Unsloth is a tool that allows users to fine-tune large language models (LLMs) 2-5x faster with 80% less memory. It is a free and open-source tool that can be used to fine-tune LLMs such as Gemma, Mistral, Llama 2-5, TinyLlama, and CodeLlama 34b. Unsloth supports 4-bit and 16-bit QLoRA / LoRA fine-tuning via bitsandbytes. It also supports DPO (Direct Preference Optimization), PPO, and Reward Modelling. Unsloth is compatible with Hugging Face's TRL, Trainer, Seq2SeqTrainer, and Pytorch code. It is also compatible with NVIDIA GPUs since 2018+ (minimum CUDA Capability 7.0).

The Alignment Handbook provides robust training recipes for continuing pretraining and aligning language models with human and AI preferences. It includes techniques such as continued pretraining, supervised fine-tuning, reward modeling, rejection sampling, and direct preference optimization (DPO). The handbook aims to fill the gap in public resources on training these models, collecting data, and measuring metrics for optimal downstream performance.

The LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** covers essential knowledge about mathematics, Python, and neural networks. 2. 🧑‍🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. For an interactive version of this course, I created two **LLM assistants** that will answer questions and test your knowledge in a personalized way: * 🤗 **HuggingChat Assistant**: Free version using Mixtral-8x7B. * 🤖 **ChatGPT Assistant**: Requires a premium account. ## 📝 Notebooks A list of notebooks and articles related to large language models. ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 LLM AutoEval | Automatically evaluate your LLMs using RunPod |  | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. |  | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. |  | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. |  | | 🌳 Model Family Tree | Visualize the family tree of merged models. |  | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. |  |

LLM-Blender is a framework for ensembling large language models (LLMs) to achieve superior performance. It consists of two modules: PairRanker and GenFuser. PairRanker uses pairwise comparisons to distinguish between candidate outputs, while GenFuser merges the top-ranked candidates to create an improved output. LLM-Blender has been shown to significantly surpass the best LLMs and baseline ensembling methods across various metrics on the MixInstruct benchmark dataset.

Ti aiuto a conoscere soluzioni per il settore HR legate alla Gamification e agli Assessment Game

Office Team Building fun: Innovative team-building app for engaging, collaborative office activities, fun and games.

I'm a whimsical math riddle master with Dall-E emblems as rewards!

First, please say "Create an agent team to do 〇〇." / 最初に「〇〇をするためのエージェントチームを作成してください」とお伝え下さい

Let's get started by telling me about your business: What do you offer? Who do you serve? ------------------------------------------------------- Need help Prompt Engineering? Reach out on LinkedIn: StephenHnilica

AI tool for designing engaging, trendy Pinterest pins.

Generates 3D stereogram pairs for parallel viewing.

2500+ word stories in target language with images, for language learning.

Level up Now. Upload a selfie for some superhero flair. Create a backstory. Select a superpower, arch-villain, and crew. Answer trivia. Pow!

Tell me about your situation and the type of prayer you would like

利用专业的周易知识和命理知识进行头像设计 Generates and explains lucky profile pictures based on I Ching, zodiac.

创建你自己的数字人形象，Sponsor：小红书“ItsJoe就出行”

I'll recreate a competitor website for your business

Create a very detailed prompt from the image. 画像からめっちゃ詳細なプロンプトを作成します。まずは解析して欲しい画像を送ってみてください。

1) Input a URL, attachment, or copy/paste a bunch of info about your biz. 2) I will return a summary of what's important. 3) Use what I give you for other prompts, e.g.: marketing strategy, content ideas, competitive analysis, etc

Create a Mythological Creature for playing with imagination and possibilities

Autonomously creates complete TikTok scenarios with images.

Simulates advisory board meetings with investors. Get generated advice for your startup from a GPT educated by domain experts.

Advisor for hairstyles, top products, and salon recommendations matched with your hair type and location.

Replicate Image, Images Mergeve, Imaginative Edit, Style Transfer. Use "Help" for more info. 20+ features of the source image will be transferred. You also can call this GPT via @ in any chat (desktop only).