Best AI tools for< Finetune Llms >

FinetuneDB is an AI fine-tuning platform that allows users to easily create and manage datasets to fine-tune LLMs, evaluate outputs, and iterate on production data. It integrates with open-source and proprietary foundation models, and provides a collaborative editor for building datasets. FinetuneDB also offers a variety of features for evaluating model performance, including human and AI feedback, automated evaluations, and model metrics tracking.

Tune AI is an enterprise Gen AI stack that offers custom models to build competitive advantage. It provides a range of features such as accelerating coding, content creation, indexing patent documents, data audit, automatic speech recognition, and more. The application leverages generative AI to help users solve real-world problems and create custom models on top of industry-leading open source models. With enterprise-grade security and flexible infrastructure, Tune AI caters to developers and enterprises looking to harness the power of AI.

Predibase is a platform for fine-tuning and serving Large Language Models (LLMs). It provides a cost-effective and efficient way to train and deploy LLMs for a variety of tasks, including classification, information extraction, customer sentiment analysis, customer support, code generation, and named entity recognition. Predibase is built on proven open-source technology, including LoRAX, Ludwig, and Horovod.

Tensoic AI is an AI tool designed for custom Large Language Models (LLMs) fine-tuning and inference. It offers ultra-fast fine-tuning and inference capabilities for enterprise-grade LLMs, with a focus on use case-specific tasks. The tool is efficient, cost-effective, and easy to use, enabling users to outperform general-purpose LLMs using synthetic data. Tensoic AI generates small, powerful models that can run on consumer-grade hardware, making it ideal for a wide range of applications.

Empower is a serverless fine-tuned LLM hosting platform that offers a developer platform for fine-tuned LLMs. It provides prebuilt task-specific base models with GPT4 level response quality, enabling users to save up to 80% on LLM bills with just 5 lines of code change. Empower allows users to own their models, offers cost-effective serving with no compromise on performance, and charges on a per-token basis. The platform is designed to be user-friendly, efficient, and cost-effective for deploying and serving fine-tuned LLMs.

Fireworks is a generative AI platform for product innovation. It provides developers with access to the world's leading generative AI models, at the fastest speeds. With Fireworks, developers can build and deploy AI-powered applications quickly and easily.

Labelbox is a data factory platform that empowers AI teams to manage data labeling, train models, and create better data with internet scale RLHF platform. It offers an all-in-one solution comprising tooling and services powered by a global community of domain experts. Labelbox operates a global data labeling infrastructure and operations for AI workloads, providing expert human network for data labeling in various domains. The platform also includes AI-assisted alignment for maximum efficiency, data curation, model training, and labeling services. Customers achieve breakthroughs with high-quality data through Labelbox.

Prem is an AI platform that empowers developers and businesses to build and fine-tune generative AI models with ease. It offers a user-friendly development platform for developers to create AI solutions effortlessly. For businesses, Prem provides tailored model fine-tuning and training to meet unique requirements, ensuring data sovereignty and ownership. Trusted by global companies, Prem accelerates the advent of sovereign generative AI by simplifying complex AI tasks and enabling full control over intellectual capital. With a suite of foundational open-source SLMs, Prem supercharges business applications with cutting-edge research and customization options.

FinetuneFast is an AI tool designed to help developers, indie makers, and businesses to efficiently finetune machine learning models, process data, and deploy AI solutions at lightning speed. With pre-configured training scripts, efficient data loading pipelines, and one-click model deployment, FinetuneFast streamlines the process of building and deploying AI models, saving users valuable time and effort. The tool is user-friendly, accessible for ML beginners, and offers lifetime updates for continuous improvement.

MagikKraft is an AI-powered platform that simplifies complex controls by allowing users to create personalized sequences and actions for programmable devices like drones, automated appliances, and self-driving vehicles. Users can craft customized recipes, test them in a virtual environment, and deploy them seamlessly into the real world. MagikKraft prioritizes privacy, user control, and creative freedom, aiming to enhance technology's potential without causing harm or unforeseen consequences.

Fine-Tune AI is a tool that allows users to generate fine-tune data sets using prompts. This can be useful for a variety of tasks, such as improving the accuracy of machine learning models or creating new training data for AI applications.

Prompteasy.ai is an AI tool that allows users to fine-tune AI models in less than 5 minutes. It simplifies the process of training AI models on user data, making it as easy as having a conversation. Users can fully customize GPT by fine-tuning it to meet their specific needs. The tool offers data-driven customization, interactive AI coaching, and seamless model enhancement, providing users with a competitive edge and simplifying AI integration into their workflows.

ReplyInbox is a Gmail Chrome extension that revolutionizes email management by harnessing the power of AI. It automates email replies based on your product or service knowledge base, saving you time and effort. Simply select the text you want to respond to, click generate, and let ReplyInbox craft a personalized and high-quality reply. You can also share website links and other documentation with ReplyInbox's AI to facilitate even more accurate and informative responses.

re:tune is a no-code AI app solution that provides everything you need to transform your business with AI, from custom chatbots to autonomous agents. With re:tune, you can build chatbots for any use case, connect any data source, and integrate with all your favorite tools and platforms. re:tune is the missing platform to build your AI apps.

Imajinn AI is a cutting-edge visualization tool that utilizes the latest in AI technology to reimagine photos and images into stunning works of art. The platform offers a suite of AI-powered products and tools, including personalized children's books, couples portraits, product visualizer, sneaker generator, and a WordPress plugin. Users can create memorable gifts, products, and experiences with Imajinn's AI-powered tools, making it easy to transform ordinary photos into extraordinary creations. Imajinn also provides users with the ability to train custom AI models, generate concept images, and download raw AI model checkpoints for further use in their applications.

Kiln is an AI tool designed for fine-tuning LLM models, generating synthetic data, and facilitating collaboration on datasets. It offers intuitive desktop apps, zero-code fine-tuning for various models, interactive visual tools for data generation, Git-based version control for datasets, and the ability to generate various prompts from data. Kiln supports a wide range of models and providers, provides an open-source library and API, prioritizes privacy, and allows structured data tasks in JSON format. The tool is free to use and focuses on rapid AI prototyping and dataset collaboration.

Gretel.ai is a synthetic data platform purpose-built for AI applications. It allows users to generate artificial, synthetic datasets with the same characteristics as real data, enabling the improvement of AI models without compromising privacy. The platform offers features such as generating data from input prompts, creating safe synthetic versions of sensitive datasets, flexible data transformation, building data pipelines, and measuring data quality. Gretel.ai is designed to help developers unlock synthetic data and achieve more with safe access to the right data.

JobHire is an AI-powered job search automation platform that helps users find and apply to relevant job openings. It uses artificial intelligence to analyze and recreate users' resumes, making them more attractive to potential employers. JobHire also automatically creates email addresses and uses them to send responses to suitable vacancies, modifying users' resumes for each specific position. Additionally, it tracks responses from employers and provides users with a dashboard to track their progress.

Helix AI is a private GenAI platform that enables users to build AI applications using open source models. The platform offers tools for RAG (Retrieval-Augmented Generation) and fine-tuning, allowing deployment on-premises or in a Virtual Private Cloud (VPC). Users can access curated models, utilize Helix API tools to connect internal and external APIs, embed Helix Assistants into websites/apps for chatbot functionality, write AI application logic in natural language, and benefit from the innovative RAG system for Q&A generation. Additionally, users can fine-tune models for domain-specific needs and deploy securely on Kubernetes or Docker in any cloud environment. Helix Cloud offers free and premium tiers with GPU priority, catering to individuals, students, educators, and companies of varying sizes.

Polarr Copilots are AI-powered tools that help you create stunning photos, videos, and designs. With Polarr Copilots, you can transform your imagination into reality with just a few simple words. Our Copilots are trained on millions of community-generated edits, so they can create unique and realistic edits that are tailored to your specific needs. Whether you're a professional photographer, a social media enthusiast, or just someone who loves to express themselves through creativity, Polarr Copilots can help you take your creative vision to the next level.

SuperAdapters is a tool designed to finetune Large Language Models (LLMs) with various adapters on different platforms. It supports models like Bloom, LLaMA, ChatGLM, Qwen, Baichuan, Mixtral, Phi, and more. Users can finetune LLMs on Windows, Linux, and Mac M1/2, handle train/test data with Terminal, File, or DataBase, and perform tasks like CausalLM and SequenceClassification. The tool provides detailed instructions on how to use different models with specific adapters for tasks like finetuning and inference. It also includes requirements for CentOS, Ubuntu, and MacOS, along with information on LLM downloads and data formats. Additionally, it offers parameters for finetuning and inference, as well as options for web and API-based inference.

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.

LLM-workshop-2024 is a tutorial designed for coders interested in understanding the building blocks of large language models (LLMs), how LLMs work, and how to code them from scratch in PyTorch. The tutorial covers topics such as introduction to LLMs, understanding LLM input data, coding LLM architecture, pretraining LLMs, loading pretrained weights, and finetuning LLMs using open-source libraries. Participants will learn to implement a small GPT-like LLM, including data input pipeline, core architecture components, and pretraining code.

LLM Alchemy Chamber is a repository dedicated to exploring the world of Language Models (LLMs) through various experiments and projects. It contains scripts, notebooks, and experiments focused on tasks such as fine-tuning different LLM models, quantization for performance optimization, dataset generation for instruction/QA tasks, and more. The repository offers a collection of resources for beginners and enthusiasts interested in delving into the mystical realm of LLMs.

LLamaTuner is a repository for the Efficient Finetuning of Quantized LLMs project, focusing on building and sharing instruction-following Chinese baichuan-7b/LLaMA/Pythia/GLM model tuning methods. The project enables training on a single Nvidia RTX-2080TI and RTX-3090 for multi-round chatbot training. It utilizes bitsandbytes for quantization and is integrated with Huggingface's PEFT and transformers libraries. The repository supports various models, training approaches, and datasets for supervised fine-tuning, LoRA, QLoRA, and more. It also provides tools for data preprocessing and offers models in the Hugging Face model hub for inference and finetuning. The project is licensed under Apache 2.0 and acknowledges contributions from various open-source contributors.

LLM-on-Ray is a comprehensive solution for building, customizing, and deploying Large Language Models (LLMs). It simplifies complex processes into manageable steps by leveraging the power of Ray for distributed computing. The tool supports pretraining, finetuning, and serving LLMs across various hardware setups, incorporating industry and Intel optimizations for performance. It offers modular workflows with intuitive configurations, robust fault tolerance, and scalability. Additionally, it provides an Interactive Web UI for enhanced usability, including a chatbot application for testing and refining models.

Awesome-LLM-Quantization is a curated list of resources related to quantization techniques for Large Language Models (LLMs). Quantization is a crucial step in deploying LLMs on resource-constrained devices, such as mobile phones or edge devices, by reducing the model's size and computational requirements.

PEFT (Parameter-Efficient Fine-Tuning) is a collection of state-of-the-art methods that enable efficient adaptation of large pretrained models to various downstream applications. By only fine-tuning a small number of extra model parameters instead of all the model's parameters, PEFT significantly decreases the computational and storage costs while achieving performance comparable to fully fine-tuned models.

This repository contains a hand-curated list of great machine (deep) learning resources for Natural Language Processing (NLP) with a focus on Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), attention mechanism, Transformer architectures/networks, Chatbot, and transfer learning in NLP.

A comprehensive repository of resources for Chinese large language models (LLMs), including data processing tools, fine-tuning frameworks, inference libraries, evaluation platforms, RAG engines, agent frameworks, books, courses, tutorials, and tips. The repository covers a wide range of tools and resources for working with LLMs, from data labeling and processing to model fine-tuning, inference, evaluation, and application development. It also includes resources for learning about LLMs through books, courses, and tutorials, as well as insights and strategies from building with LLMs.

Awesome GPT + Security is a curated list of awesome security tools, experimental case or other interesting things with LLM or GPT. It includes tools for integrated security, auditing, reconnaissance, offensive security, detecting security issues, preventing security breaches, social engineering, reverse engineering, investigating security incidents, fixing security vulnerabilities, assessing security posture, and more. The list also includes experimental cases, academic research, blogs, and fun projects related to GPT security. Additionally, it provides resources on GPT security standards, bypassing security policies, bug bounty programs, cracking GPT APIs, and plugin security.

Awesome-LLM is a curated list of resources related to large language models, focusing on papers, projects, frameworks, tools, tutorials, courses, opinions, and other useful resources in the field. It covers trending LLM projects, milestone papers, other papers, open LLM projects, LLM training frameworks, LLM evaluation frameworks, tools for deploying LLM, prompting libraries & tools, tutorials, courses, books, and opinions. The repository provides a comprehensive overview of the latest advancements and resources in the field of large language models.

DB-GPT is an open source AI native data app development framework with AWEL(Agentic Workflow Expression Language) and agents. It aims to build infrastructure in the field of large models, through the development of multiple technical capabilities such as multi-model management (SMMF), Text2SQL effect optimization, RAG framework and optimization, Multi-Agents framework collaboration, AWEL (agent workflow orchestration), etc. Which makes large model applications with data simpler and more convenient.

AITreasureBox is a comprehensive collection of AI tools and resources designed to simplify and accelerate the development of AI projects. It provides a wide range of pre-trained models, datasets, and utilities that can be easily integrated into various AI applications. With AITreasureBox, developers can quickly prototype, test, and deploy AI solutions without having to build everything from scratch. Whether you are working on computer vision, natural language processing, or reinforcement learning projects, AITreasureBox has something to offer for everyone. The repository is regularly updated with new tools and resources to keep up with the latest advancements in the field of artificial intelligence.

This project provides a comprehensive guide to fine-tuning large language models (LLMs) with efficient methods like LoRA and P-tuning V2. It includes detailed instructions, code examples, and performance benchmarks for various LLMs and fine-tuning techniques. The guide also covers data preparation, evaluation, prediction, and running inference on CPU environments. By leveraging this guide, users can effectively fine-tune LLMs for specific tasks and applications.

H2O LLM Studio is a framework and no-code GUI designed for fine-tuning state-of-the-art large language models (LLMs). With H2O LLM Studio, you can easily and effectively fine-tune LLMs without the need for any coding experience. The GUI is specially designed for large language models, and you can finetune any LLM using a large variety of hyperparameters. You can also use recent finetuning techniques such as Low-Rank Adaptation (LoRA) and 8-bit model training with a low memory footprint. Additionally, you can use Reinforcement Learning (RL) to finetune your model (experimental), use advanced evaluation metrics to judge generated answers by the model, track and compare your model performance visually, and easily export your model to the Hugging Face Hub and share it with the community.

LitGPT is a command-line tool designed to easily finetune, pretrain, evaluate, and deploy 20+ LLMs **on your own data**. It features highly-optimized training recipes for the world's most powerful open-source large-language-models (LLMs).

The fsdp_qlora repository provides a script for training Large Language Models (LLMs) with Quantized LoRA and Fully Sharded Data Parallelism (FSDP). It integrates FSDP+QLoRA into the Axolotl platform and offers installation instructions for dependencies like llama-recipes, fastcore, and PyTorch. Users can finetune Llama-2 70B on Dual 24GB GPUs using the provided command. The script supports various training options including full params fine-tuning, LoRA fine-tuning, custom LoRA fine-tuning, quantized LoRA fine-tuning, and more. It also discusses low memory loading, mixed precision training, and comparisons to existing trainers. The repository addresses limitations and provides examples for training with different configurations, including BnB QLoRA and HQQ QLoRA. Additionally, it offers SLURM training support and instructions for adding support for a new model.

LLM Foundry is a codebase for training, finetuning, evaluating, and deploying LLMs for inference with Composer and the MosaicML platform. It is designed to be easy-to-use, efficient _and_ flexible, enabling rapid experimentation with the latest techniques. You'll find in this repo: * `llmfoundry/` - source code for models, datasets, callbacks, utilities, etc. * `scripts/` - scripts to run LLM workloads * `data_prep/` - convert text data from original sources to StreamingDataset format * `train/` - train or finetune HuggingFace and MPT models from 125M - 70B parameters * `train/benchmarking` - profile training throughput and MFU * `inference/` - convert models to HuggingFace or ONNX format, and generate responses * `inference/benchmarking` - profile inference latency and throughput * `eval/` - evaluate LLMs on academic (or custom) in-context-learning tasks * `mcli/` - launch any of these workloads using MCLI and the MosaicML platform * `TUTORIAL.md` - a deeper dive into the repo, example workflows, and FAQs

This repository provides a comprehensive guide to training, evaluating, and building applications with Large Language Models (LLMs). It covers various aspects of LLMs, including pretraining, fine-tuning, reinforcement learning from human feedback (RLHF), and more. The repository also includes practical examples and code snippets to help users get started with LLMs quickly and easily.

A witty editor to fine-tune stand-up comedy jokes.

Untangle Your Ethical Knots and 'Fine-Tune' Your Values with JustInGPT

I'm Chic Strategic, your ally in carving out a distinct brand position and fine-tuning your voice. Let's make your brand's presence robust and its message clear in a bustling market.

👉AI绘画，无视版权，精准创作提示词。👈1.可描述画面2.可给出midjourney的绘画提示词3.为每幅画作指定专属 ID，便于精调4.可以画绘制皮克斯拟人可爱动物。1. Can describe the picture . 2. Can give the prompt words for midjourney's painting . 3. Assign a unique ID to each painting to facilitate fine-tuning

An assistant to help you understand transfer learning better

Your purpose is to create the pytorch code to train language models using pytorch

大型语言模型的学习和训练指导专家

A witty yet succinct guide for HuggingFace, offering technical assistance on using the platform - based on their Learning Hub

Expert in refining custom GPT model instructions.