Best AI tools for< Train Your Own Models >

Scruffy AI is a website that allows users to create custom dog portraits and gifts. Users can select from a variety of portrait styles, upload pictures of their dogs, and then choose their favorite portrait to download. Scruffy AI also offers both digital and framed prints. The website is easy to use and provides high-quality results. Users can also use Scruffy AI to train their own models to generate new images.

OpenAI Platform is a suite of powerful AI tools that can help you build and deploy AI applications. With OpenAI Platform, you can access state-of-the-art AI models, including GPT-3, Codex, and DALL-E 2. You can also use OpenAI Platform to train your own custom AI models. OpenAI Platform is used by businesses of all sizes to build a wide range of AI applications, including chatbots, language translation tools, and image generators.

SentiSight.ai is a machine learning platform for image recognition solutions, offering services such as object detection, image segmentation, image classification, image similarity search, image annotation, computer vision consulting, and intelligent automation consulting. Users can access pre-trained models, background removal, NSFW detection, text recognition, and image recognition API. The platform provides tools for image labeling, project management, and training tutorials for various image recognition models. SentiSight.ai aims to streamline the image annotation process, empower users to build and train their own models, and deploy them for online or offline use.

ModaMind is an AI platform designed specifically for fashion designers, offering an innovative fashion design assistant powered by advanced AI algorithms. The platform enables designers to create unique fashion designs tailored to their style, providing endless design ideas from prompts or images. By automating the design ideation process and incorporating the latest trends, ModaMind helps designers accelerate time to market, keep up with recent trends, and meet customer needs. With features like style personalization, AI intelligent garment design, custom visual studio, and the ability to train your own AI model, ModaMind empowers designers to create and innovate with ease.

HappyAccidents is an AI-powered art generation tool that makes it easy to create stunning images from text prompts. With HappyAccidents, you can generate images from any open-source model, train your own embeddings, and use powerful features like inpainting and upscaling. HappyAccidents is perfect for artists, designers, and anyone who wants to create beautiful images without the hassle of learning complex AI models.

Imajinn AI is a cutting-edge visualization tool that utilizes fine-tuned AI technology to reimagine photos and images into stunning works of art. The platform offers a suite of AI-powered tools for creating personalized children's books, couples portraits, product visualizations, sneaker designs, and more. Users can easily generate concept images, train custom AI models, and access a variety of presets for high-quality outputs. Imajinn AI is designed to empower users to bring their creative ideas to life with ease and efficiency.

DeepMode.ai is a platform that allows users to create their own AI clone models. With DeepMode.ai, users can train AI models on their own data, and then use those models to automate tasks, make predictions, and generate new content. DeepMode.ai is designed to be easy to use, even for users with no prior experience with AI. The platform provides a variety of tools and resources to help users get started, including tutorials, documentation, and a community forum.

Mirage is a custom AI platform that builds custom LLMs to accelerate productivity. It is backed by Sequoia and offers a variety of features, including the ability to create custom AI models, train models on your own data, and deploy models to the cloud or on-premises.

Arcee AI is a platform that offers a cost-effective, secure, end-to-end solution for building and deploying Small Language Models (SLMs). It allows users to merge and train custom language models by leveraging open source models and their own data. The platform is known for its Model Merging technique, which combines the power of pre-trained Large Language Models (LLMs) with user-specific data to create high-performing models across various industries.

Teachable Machine is a web-based tool that makes it easy to create custom machine learning models, even if you don't have any coding experience. With Teachable Machine, you can train models to recognize images, sounds, and poses. Once you've trained a model, you can export it to use in your own projects.

CustomGPT.ai is a no-code platform that allows businesses to create their own custom ChatGPT chatbots using their own business content. The platform is powered by GPT-4 and provides a range of features, including the ability to upload documents, integrate with other systems, and customize the chatbot's appearance and behavior. CustomGPT.ai is designed to help businesses improve customer service, employee efficiency, and knowledge management.

Tess is the first AI image generator that empowers artists to own their style by creating properly-licensed images. It offers a world-class image editor designed for AI, allowing users to generate art in a consistent visual style. Tess enables artists to create models, edit and customize their generations, and discover how AI can enhance their artistic style. With Tess, users can access copyright-safe generations created by real artists, ensuring ethical AI art practices.

KZHU.ai is an online learning platform that offers a variety of courses in artificial intelligence, machine learning, data science, and other related fields. The platform is designed for both beginners and experienced professionals who want to learn more about AI and its applications.

OpenArt is an AI-powered art platform that offers a free AI image generator and editor. It allows users to create images using pre-built models or by training their own models. The platform provides an intuitive AI drawing tool and editing suite to transform artistic concepts into reality. OpenArt stands out for its boundary-free AI drawing, advanced AI art tools, diverse artistic styles, and the ability to train custom AI models. It caters to both amateur and professional artists, offering high-quality art creation and comprehensive support. Users can experiment with various styles, receive detailed feedback, and collaborate on artistic projects through the platform.

Unless is a conversational AI platform that helps organizations unlock their knowledge and provide better customer support. With Unless, you can train an AI model with your own knowledge base, documents, or website, and then let your customers or team engage in conversations with the AI through various channels. Unless is designed to be easy to use, even for non-technical staff, and it offers a variety of features to help you get the most out of your AI model.

Amazon SageMaker Python SDK is an open source library for training and deploying machine-learned models on Amazon SageMaker. With the SDK, you can train and deploy models using popular deep learning frameworks, algorithms provided by Amazon, or your own algorithms built into SageMaker-compatible Docker images.

Chat Data is an AI application that allows users to create custom chatbots using their own data sources. Users can easily build and integrate chatbots with their websites or other platforms, personalize the chatbot's interface, and access advanced features like human support escalation and product updates synchronization. The platform offers HIPAA-compliant medical chat models and ensures data privacy by retaining conversation data exclusively within the user's browser. With Chat Data, users can enhance customer interactions, gather insights, and streamline communication processes.

Kaba.ai is an AI-driven foundation that enables users to create and own a Human-like Model (HLM) that updates, retrains, and applies in real-time as users navigate their lives. The platform aims to mimic how humans function to fully harness the power of AI. Kaba offers features such as Human-like Models, Unified Experience, Full Ownership, Contextual Data, and a personalized journey focused on speed, security, and personalization.

LunaGPT is a cutting-edge automation tool powered by ChatGPT, designed to revolutionize customer support and lead generation. It allows users to train their own GPT chatbot on their data, enabling it to provide instant, friendly, and precise answers to customers 24/7. LunaGPT offers a state-of-the-art SaaS platform that can be customized to unlock the true potential of products. With powerful AI capabilities, including access to OpenAI conversational models like GPT-3.5-turbo and GPT-4, LunaGPT is a comprehensive solution for businesses looking to supercharge their customer support and lead generation efforts.

B-Bot is an innovative platform that empowers businesses and individuals to easily create and manage AI solutions. With a focus on accessibility and fairness, B-Bot streamlines the AI development process, making advanced technology available to everyone. Users can build their own Virtual Experts, train them, and profit from their capabilities. The platform also offers integration with various AI models and databases for enhanced functionality and automation. Join the B-Bot community to exchange ideas, network, and shape the future together.

LL3DA is a Large Language 3D Assistant that responds to both visual and textual interactions within complex 3D environments. It aims to help Large Multimodal Models (LMM) comprehend, reason, and plan in diverse 3D scenes by directly taking point cloud input and responding to textual instructions and visual prompts. LL3DA achieves remarkable results in 3D Dense Captioning and 3D Question Answering, surpassing various 3D vision-language models. The code is fully released, allowing users to train customized models and work with pre-trained weights. The tool supports training with different LLM backends and provides scripts for tuning and evaluating models on various tasks.

spaCy is an industrial-strength Natural Language Processing (NLP) library in Python and Cython. It incorporates the latest research and is designed for real-world applications. The library offers pretrained pipelines supporting 70+ languages, with advanced neural network models for tasks such as tagging, parsing, named entity recognition, and text classification. It also facilitates multi-task learning with pretrained transformers like BERT, along with a production-ready training system and streamlined model packaging, deployment, and workflow management. spaCy is commercial open-source software released under the MIT license.

MOOSE 2.0 is a leaner, meaner, and stronger tool for 3D medical image segmentation. It is built on the principles of data-centric AI and offers a wide range of segmentation models for both clinical and preclinical settings. MOOSE 2.0 is also versatile, allowing users to use it as a command-line tool for batch processing or as a library package for individual processing in Python projects. With its improved speed, accuracy, and flexibility, MOOSE 2.0 is the go-to tool for segmentation tasks.

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.

CosyVoice is a tool designed for speech synthesis, offering pretrained models for zero-shot, sft, instruct inference. It provides a web demo for easy usage and supports advanced users with train and inference scripts. The tool can be deployed using grpc for service deployment. Users can download pretrained models and resources for immediate use or train their own models from scratch. CosyVoice is suitable for researchers, developers, linguists, AI engineers, and speech technology enthusiasts.

MockingBird is a toolbox designed for Mandarin speech synthesis using PyTorch. It supports multiple datasets such as aidatatang_200zh, magicdata, aishell3, and data_aishell. The toolbox can run on Windows, Linux, and M1 MacOS, providing easy and effective speech synthesis with pretrained encoder/vocoder models. It is webserver ready for remote calling. Users can train their own models or use existing ones for the encoder, synthesizer, and vocoder. The toolbox offers a demo video and detailed setup instructions for installation and model training.

Deep Lake is a Database for AI powered by a storage format optimized for deep-learning applications. Deep Lake can be used for: 1. Storing data and vectors while building LLM applications 2. Managing datasets while training deep learning models Deep Lake simplifies the deployment of enterprise-grade LLM-based products by offering storage for all data types (embeddings, audio, text, videos, images, pdfs, annotations, etc.), querying and vector search, data streaming while training models at scale, data versioning and lineage, and integrations with popular tools such as LangChain, LlamaIndex, Weights & Biases, and many more. Deep Lake works with data of any size, it is serverless, and it enables you to store all of your data in your own cloud and in one place. Deep Lake is used by Intel, Bayer Radiology, Matterport, ZERO Systems, Red Cross, Yale, & Oxford.

Distilabel is a framework for synthetic data and AI feedback for AI engineers that require high-quality outputs, full data ownership, and overall efficiency. It helps you synthesize data and provide AI feedback to improve the quality of your AI models. With Distilabel, you can: * **Synthesize data:** Generate synthetic data to train your AI models. This can help you to overcome the challenges of data scarcity and bias. * **Provide AI feedback:** Get feedback from AI models on your data. This can help you to identify errors and improve the quality of your data. * **Improve your AI output quality:** By using Distilabel to synthesize data and provide AI feedback, you can improve the quality of your AI models and get better results.

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. |  |

This repository provides all the necessary items to build a Language Model from scratch, inspired by Karpathy's nanoGPT and Shakespeare generator. It includes data collection tools, data processing scripts, various models like BERT, GPT, and Seq-2-Seq, along with tokenizer and training files.

SkyPilot is a framework for running LLMs, AI, and batch jobs on any cloud, offering maximum cost savings, highest GPU availability, and managed execution. SkyPilot abstracts away cloud infra burdens: - Launch jobs & clusters on any cloud - Easy scale-out: queue and run many jobs, automatically managed - Easy access to object stores (S3, GCS, R2) SkyPilot maximizes GPU availability for your jobs: * Provision in all zones/regions/clouds you have access to (the _Sky_), with automatic failover SkyPilot cuts your cloud costs: * Managed Spot: 3-6x cost savings using spot VMs, with auto-recovery from preemptions * Optimizer: 2x cost savings by auto-picking the cheapest VM/zone/region/cloud * Autostop: hands-free cleanup of idle clusters SkyPilot supports your existing GPU, TPU, and CPU workloads, with no code changes.

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.

The STM32 AI model zoo is a collection of reference machine learning models optimized to run on STM32 microcontrollers. It provides a large collection of application-oriented models ready for re-training, scripts for easy retraining from user datasets, pre-trained models on reference datasets, and application code examples generated from user AI models. The project offers training scripts for transfer learning or training custom models from scratch. It includes performances on reference STM32 MCU and MPU for float and quantized models. The project is organized by application, providing step-by-step guides for training and deploying models.

Anima is the first open-source 33B Chinese large language model based on QLoRA, supporting DPO alignment training and open-sourcing a 100k context window model. The latest update includes AirLLM, a library that enables inference of 70B LLM from a single GPU with just 4GB memory. The tool optimizes memory usage for inference, allowing large language models to run on a single 4GB GPU without the need for quantization or other compression techniques. Anima aims to democratize AI by making advanced models accessible to everyone and contributing to the historical process of AI democratization.

LLMBox is a comprehensive library designed for implementing Large Language Models (LLMs) with a focus on a unified training pipeline and comprehensive model evaluation. It serves as a one-stop solution for training and utilizing LLMs, offering flexibility and efficiency in both training and utilization stages. The library supports diverse training strategies, comprehensive datasets, tokenizer vocabulary merging, data construction strategies, parameter efficient fine-tuning, and efficient training methods. For utilization, LLMBox provides comprehensive evaluation on various datasets, in-context learning strategies, chain-of-thought evaluation, evaluation methods, prefix caching for faster inference, support for specific LLM models like vLLM and Flash Attention, and quantization options. The tool is suitable for researchers and developers working with LLMs for natural language processing tasks.

YGO Agent is a project focused on using deep learning to master the Yu-Gi-Oh! trading card game. It utilizes reinforcement learning and large language models to develop advanced AI agents that aim to surpass human expert play. The project provides a platform for researchers and players to explore AI in complex, strategic game environments.

Awesome LLM Courses is a curated list of online courses focused on Large Language Models (LLMs). The repository aims to provide a comprehensive collection of free available courses covering various aspects of LLMs, including fundamentals, engineering, and applications. The courses are suitable for individuals interested in natural language processing, AI development, and machine learning. The list includes courses from reputable platforms such as Hugging Face, Udacity, DeepLearning.AI, Cohere, DataCamp, and more, offering a wide range of topics from pretraining LLMs to building AI applications with LLMs. Whether you are a beginner looking to understand the basics of LLMs or an intermediate developer interested in advanced topics like prompt engineering and generative AI, this repository has something for everyone.

This repository contains a minimal, clean code implementation of the Byte Pair Encoding (BPE) algorithm, commonly used in LLM tokenization. The BPE algorithm is "byte-level" because it runs on UTF-8 encoded strings. This algorithm was popularized for LLMs by the GPT-2 paper and the associated GPT-2 code release from OpenAI. Sennrich et al. 2015 is cited as the original reference for the use of BPE in NLP applications. Today, all modern LLMs (e.g. GPT, Llama, Mistral) use this algorithm to train their tokenizers. There are two Tokenizers in this repository, both of which can perform the 3 primary functions of a Tokenizer: 1) train the tokenizer vocabulary and merges on a given text, 2) encode from text to tokens, 3) decode from tokens to text. The files of the repo are as follows: 1. minbpe/base.py: Implements the `Tokenizer` class, which is the base class. It contains the `train`, `encode`, and `decode` stubs, save/load functionality, and there are also a few common utility functions. This class is not meant to be used directly, but rather to be inherited from. 2. minbpe/basic.py: Implements the `BasicTokenizer`, the simplest implementation of the BPE algorithm that runs directly on text. 3. minbpe/regex.py: Implements the `RegexTokenizer` that further splits the input text by a regex pattern, which is a preprocessing stage that splits up the input text by categories (think: letters, numbers, punctuation) before tokenization. This ensures that no merges will happen across category boundaries. This was introduced in the GPT-2 paper and continues to be in use as of GPT-4. This class also handles special tokens, if any. 4. minbpe/gpt4.py: Implements the `GPT4Tokenizer`. This class is a light wrapper around the `RegexTokenizer` (2, above) that exactly reproduces the tokenization of GPT-4 in the tiktoken library. The wrapping handles some details around recovering the exact merges in the tokenizer, and the handling of some unfortunate (and likely historical?) 1-byte token permutations. Finally, the script train.py trains the two major tokenizers on the input text tests/taylorswift.txt (this is the Wikipedia entry for her kek) and saves the vocab to disk for visualization. This script runs in about 25 seconds on my (M1) MacBook. All of the files above are very short and thoroughly commented, and also contain a usage example on the bottom of the file.

Embedded inference of Deep Learning models is quite challenging due to high compute requirements. TI’s Edge AI software product helps optimize and accelerate inference on TI’s embedded devices. It supports heterogeneous execution of DNNs across cortex-A based MPUs, TI’s latest generation C7x DSP, and DNN accelerator (MMA). The solution simplifies the product life cycle of DNN development and deployment by providing a rich set of tools and optimized libraries.

BABILong is a generative benchmark designed to evaluate the performance of NLP models in processing long documents with distributed facts. It consists of 20 tasks that simulate interactions between characters and objects in various locations, requiring models to distinguish important information from irrelevant details. The tasks vary in complexity and reasoning aspects, with test samples potentially containing millions of tokens. The benchmark aims to challenge and assess the capabilities of Large Language Models (LLMs) in handling complex, long-context information.

Expert in pet training advice, friendly and engaging.

I'm a voice coach here to train your voice.

A dog training assistant.

Social Ads Trainer

Vorstellungskraft trainieren und Denkweisen durchbrechen.

Specialist in interpreting and improving pet behavior

Text your favorite pet, after answering 10 questions about their everyday lives!

Your virtual mouth helps you taste everything you want to try

I provide dog health and care tips.

Golden Retriever training expert providing advice and tips

A dog whisperer offering insights on canine behavior and training.

Helps users select the right Social Movement Technologies training.

Offers tailored advice on pet care, training, and health.

The go-to GPT for pet owners. Everything pet related in one place

Woof! Pawsome facts and adorable doggo pics!

Breed Selector & Lifestyle Advisor

I interpret dog behaviors and vocalizations in a fun, professional way.

Friendly train travel guide focusing on the best routes, essential travel information, and personalized travel insights, for both experienced and novice travelers.

Your personal advisor for eco-friendly train travel. Let's plan your next journey together!

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