Best AI tools for< Fine-tune On Datasets >

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.

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.

Gretel.ai is an AI tool that helps users incorporate generative AI into their data by generating synthetic data that is as good or better than the existing data. Users can fine-tune custom AI models and use Gretel's APIs to generate unlimited synthesized datasets, perform privacy-preserving transformations on sensitive data, and identify PII with advanced NLP detection. Gretel's APIs make it simple to generate anonymized and safe synthetic data, allowing users to innovate faster and preserve privacy while doing it. Gretel's platform includes Synthetics, Transform, and Classify APIs that provide users with a complete set of tools to create safe data. Gretel also offers a range of resources, including documentation, tutorials, GitHub projects, and open-source SDKs for developers. Gretel Cloud runners allow users to keep data contained by running Gretel containers in their environment or scaling out workloads to the cloud in seconds. Overall, Gretel.ai is a powerful AI tool for generating synthetic data that can help users unlock innovation and achieve more with safe access to the right data.

Defog.ai provides fine-tuned AI models for enterprise SQL. It helps businesses speed up data analyses in SQL, Python, and R with AI assistants and agents tailored for their business - without sharing their data. Defog.ai's key features include the ability to ask questions of data in natural language, get results when needed, integrate with any SQL database or data warehouse, automatically visualize data as tables and charts, and fine-tune on your metadata to give results you can trust.

poolside is an advanced foundational AI model designed specifically for software engineering challenges. It allows users to fine-tune the model on their own code, enabling it to understand project uniqueness and complexities that generic models can't grasp. The platform aims to empower teams to build better, faster, and happier by providing a personalized AI model that continuously improves. In addition to the AI model for writing code, poolside offers an intuitive editor assistant and an API for developers to leverage.

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.

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.

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.

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.

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.

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.

Neurons is an AI tool designed to help marketers and designers optimize their creatives and improve campaign effectiveness. It provides instant visual feedback, data-driven insights, and scalable attention predictions rooted in neuroscience. The platform is built on the latest advances in cognitive neuroscience, machine learning, AI, and psychology, ensuring scientific validity in its methods and metrics. Neurons aims to reduce guesswork, increase impact, and enable users to make better decisions faster.

OpenLIT is an AI application designed as an Observability tool for GenAI and LLM applications. It empowers model understanding and data visualization through an interactive Learning Interpretability Tool. With OpenTelemetry-native support, it seamlessly integrates into projects, offering features like fine-tuning performance, real-time data streaming, low latency processing, and visualizing data insights. The tool simplifies monitoring with easy installation and light/dark mode options, connecting to popular observability platforms for data export. Committed to OpenTelemetry community standards, OpenLIT provides valuable insights to enhance application performance and reliability.

Dynamiq is an operating platform for GenAI applications that enables users to build compliant GenAI applications in their own infrastructure. It offers a comprehensive suite of features including rapid prototyping, testing, deployment, observability, and model fine-tuning. The platform helps streamline the development cycle of AI applications and provides tools for workflow automations, knowledge base management, and collaboration. Dynamiq is designed to optimize productivity, reduce AI adoption costs, and empower organizations to establish AI ahead of schedule.

Telechat is a platform that allows users to create and deploy custom chatbots on Telegram. With Telechat, users can upload their own data, fine-tune the knowledge base, and customize the chatbot's personality. Telechat also provides a range of features to help users connect their chatbots to Telegram and other channels. Telechat is suitable for a variety of use cases, including customer support, internal knowledge bases, and community engagement.

LeadShark is an AI-powered B2B sales automation tool that helps businesses automate lead generation processes. By using a Browser Extension powered by AI, LeadShark enables users to sit back and watch high-quality leads roll into their sales funnel. The tool offers features such as automated lead generation, opportunity dashboard for sales metrics, integrations with favorite browsers, and a Go-to-Market Strategy Template for enhancing marketing strategies. LeadShark aims to address the continuous need for finding high-quality leads in outbound sales by providing automated lead generation solutions based on the user's Ideal Customer Profile criteria.

Twelve Labs is a cutting-edge AI tool that specializes in multimodal AI for video understanding. It offers state-of-the-art video foundation models and APIs to power intelligent video applications. With Twelve Labs, users can easily search, generate, and classify video content, enabling them to find specific scenes, generate accurate text summaries, and classify videos by categories. The tool is highly customizable, scalable, and secure, making it suitable for businesses with large video libraries looking to enhance their video analysis capabilities.

SD3 Medium is an advanced text-to-image model developed by Stability AI. It offers a cutting-edge approach to generating high-quality, photorealistic images based on textual prompts. The model is equipped with 2 billion parameters, ensuring exceptional quality and resource efficiency. SD3 Medium is currently in a research preview phase, primarily catering to educational and creative purposes. Users can access the model through various licensing options and explore its capabilities via the Stability Platform.

TRACE is a temporal grounding video model that utilizes causal event modeling to capture videos' inherent structure. It presents a task-interleaved video LLM model tailored for sequential encoding/decoding of timestamps, salient scores, and textual captions. The project includes various model checkpoints for different stages and fine-tuning on specific datasets. It provides evaluation codes for different tasks like VTG, MVBench, and VideoMME. The repository also offers annotation files and links to raw videos preparation projects. Users can train the model on different tasks and evaluate the performance based on metrics like CIDER, METEOR, SODA_c, F1, mAP, Hit@1, etc. TRACE has been enhanced with trace-retrieval and trace-uni models, showing improved performance on dense video captioning and general video understanding tasks.

J.A.R.V.I.S. is an offline large language model fine-tuned on custom and open datasets to mimic Jarvis's dialog with Stark. It prioritizes privacy by running locally and excels in responding like Jarvis with a similar tone. Current features include time/date queries, web searches, playing YouTube videos, and webcam image descriptions. Users can interact with Jarvis via command line after installing the model locally using Ollama. Future plans involve voice cloning, voice-to-text input, and deploying the voice model as an API.

Prometheus-Eval is a repository dedicated to evaluating large language models (LLMs) in generation tasks. It provides state-of-the-art language models like Prometheus 2 (7B & 8x7B) for assessing in pairwise ranking formats and achieving high correlation scores with benchmarks. The repository includes tools for training, evaluating, and using these models, along with scripts for fine-tuning on custom datasets. Prometheus aims to address issues like fairness, controllability, and affordability in evaluations by simulating human judgments and proprietary LM-based assessments.

SuperDuperDB is a Python framework for integrating AI models, APIs, and vector search engines directly with your existing databases, including hosting of your own models, streaming inference and scalable model training/fine-tuning. Build, deploy and manage any AI application without the need for complex pipelines, infrastructure as well as specialized vector databases, and moving our data there, by integrating AI at your data's source: - Generative AI, LLMs, RAG, vector search - Standard machine learning use-cases (classification, segmentation, regression, forecasting recommendation etc.) - Custom AI use-cases involving specialized models - Even the most complex applications/workflows in which different models work together SuperDuperDB is **not** a database. Think `db = superduper(db)`: SuperDuperDB transforms your databases into an intelligent platform that allows you to leverage the full AI and Python ecosystem. A single development and deployment environment for all your AI applications in one place, fully scalable and easy to manage.

Me LLaMA introduces a suite of open-source medical Large Language Models (LLMs), including Me LLaMA 13B/70B and their chat-enhanced versions. Developed through innovative continual pre-training and instruction tuning, these models leverage a vast medical corpus comprising PubMed papers, medical guidelines, and general domain data. Me LLaMA sets new benchmarks on medical reasoning tasks, making it a significant asset for medical NLP applications and research. The models are intended for computational linguistics and medical research, not for clinical decision-making without validation and regulatory approval.

RankLLM is a suite of prompt-decoders compatible with open source LLMs like Vicuna and Zephyr. It allows users to create custom ranking models for various NLP tasks, such as document reranking, question answering, and summarization. The tool offers a variety of features, including the ability to fine-tune models on custom datasets, use different retrieval methods, and control the context size and variable passages. RankLLM is easy to use and can be integrated into existing NLP pipelines.

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.

AI Audio Datasets List (AI-ADL) is a comprehensive collection of datasets consisting of speech, music, and sound effects, used for Generative AI, AIGC, AI model training, and audio applications. It includes datasets for speech recognition, speech synthesis, music information retrieval, music generation, audio processing, sound synthesis, and more. The repository provides a curated list of diverse datasets suitable for various AI audio tasks.

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.

AiTreasureBox is a versatile AI tool that provides a collection of pre-trained models and algorithms for various machine learning tasks. It simplifies the process of implementing AI solutions by offering ready-to-use components that can be easily integrated into projects. With AiTreasureBox, users can quickly prototype and deploy AI applications without the need for extensive knowledge in machine learning or deep learning. The tool covers a wide range of tasks such as image classification, text generation, sentiment analysis, object detection, and more. It is designed to be user-friendly and accessible to both beginners and experienced developers, making AI development more efficient and accessible to a wider audience.

Detoxify is a library that provides trained models and code to predict toxic comments on 3 Jigsaw challenges: Toxic comment classification, Unintended Bias in Toxic comments, Multilingual toxic comment classification. It includes models like 'original', 'unbiased', and 'multilingual' trained on different datasets to detect toxicity and minimize bias. The library aims to help in stopping harmful content online by interpreting visual content in context. Users can fine-tune the models on carefully constructed datasets for research purposes or to aid content moderators in flagging out harmful content quicker. The library is built to be user-friendly and straightforward to use.

LLM_QLoRA is a repository for fine-tuning Large Language Models (LLMs) using QLoRA methodology. It provides scripts for training LLMs on custom datasets, pushing models to HuggingFace Hub, and performing inference. Additionally, it includes models trained on HuggingFace Hub, a blog post detailing the QLoRA fine-tuning process, and instructions for converting and quantizing models. The repository also addresses troubleshooting issues related to Python versions and dependencies.

Kiln is an intuitive tool for fine-tuning LLM models, generating synthetic data, and collaborating on datasets. It offers desktop apps for Windows, MacOS, and Linux, zero-code fine-tuning for various models, interactive data generation, and Git-based version control. Users can easily collaborate with QA, PM, and subject matter experts, generate auto-prompts, and work with a wide range of models and providers. The tool is open-source, privacy-first, and supports structured data tasks in JSON format. Kiln is free to use and helps build high-quality AI products with datasets, facilitates collaboration between technical and non-technical teams, allows comparison of models and techniques without code, ensures structured data integrity, and prioritizes user privacy.

FiftyOne is an open-source tool designed for building high-quality datasets and computer vision models. It supercharges machine learning workflows by enabling users to visualize datasets, interpret models faster, and improve efficiency. With FiftyOne, users can explore scenarios, identify failure modes, visualize complex labels, evaluate models, find annotation mistakes, and much more. The tool aims to streamline the process of improving machine learning models by providing a comprehensive set of features for data analysis and model interpretation.

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.

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.

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

大型语言模型的学习和训练指导专家

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

Expert in refining custom GPT model instructions.

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A Michelin-starred chef offering French-style plating and recipes.

Boundary Coach is now fine-tuned and ready for use! It's an advanced guide for assertive boundary setting, offering nuanced advice, practical tips, and interactive exercises. It will provide tailored guidance, avoiding medical or legal advice and suggesting professional help when needed.

Enter the world of Secret Somm, where intrigue and fine wine meet. Whether you're a rookie or a connoisseur, your personal wine agent awaits—ready to unveil the secrets of the perfect pour. Your mission, should you choose to accept it, will lead to unparalleled wine discoveries.

Tell us your favourite animal and let us create some fine banknotes for you !

Designed for excellence in Quality Assurance, fine-tuning custom GPT configurations through continuous refinement.

Doing art design and research, including fine arts, audio arts and video arts, designed by Prof. Dr. Fred Y. Ye (Ying Ye)

It acts as an instructor guiding you through music production skills, such as fine-tuning parameters in mixing, mastering, and compression. Additionally, it functions as an aide, offering advice for your music production hurdles with just a screenshot of your production or parameter settings.

Your innovative partner for viral ad copywriting! Dive into viral marketing strategies fine-tuned to your needs!

华体科技灵感的GPT创建与精细调整专家。