Best AI tools for< Toy Collector >

The AI Funko Pop Generator is a free image generator powered by artificial intelligence. It allows users to create personalized Funko Pop figurine images by inputting text descriptions of characters, outfits, accessories, and other matching options. The generator utilizes an artificial neural network trained on a large dataset of image-text pairs to interpret user prompts and generate new Funko Pop images that mimic the Funko Pop art style. Users can create their own custom Funko Pop designs quickly and easily, without the need to log in. The application prioritizes user privacy by not collecting or using any personal information.

Bricksee is a mobile application designed to help LEGO enthusiasts organize and manage their brick sets efficiently. Users can easily reorganize their bricks, recover hidden bricks, access in-depth part information, and view detailed set information. With over 10,000 sets available for search and organization, Bricksee aims to streamline the process of rebuilding LEGO sets and enhancing the overall user experience.

ToyPal is an AI-powered storytelling toy designed for kids to enhance their learning experience and promote positive habits. It allows parents to craft personalized stories featuring their child's name, guiding them towards healthy routines. The application focuses on improving children's behavior through engaging and imaginative storytelling, creating a unique bond between the child and their favorite soft toy. ToyPal offers a safe and screen-free environment, with a rich library of 500+ free stories and a supportive parent community.

TalkDirtyAI is an AI-powered chatbot that allows users to explore their fantasies through simulated conversations. It is designed to provide a safe and private space for users to explore their sexuality and desires without judgment. The chatbot is trained on a massive dataset of erotic literature and is able to generate realistic and engaging conversations. It can also learn about the user's preferences over time and tailor the conversations accordingly.

Drawings Alive is an AI-powered application that brings children's drawings to life by transforming simple sketches into vibrant artworks. Users can upload a picture or scan of their child's drawing, provide a short description or art reference image to guide the AI, and witness the magic as the sketch is transformed into a beautiful artwork in seconds. With different subscription plans available, Drawings Alive offers up to 500 generations per month, allowing parents to spark their child's creativity and imagination effortlessly.

Face To Many is an AI-powered image generator that allows users to create multiple styles of their own images. With Face To Many, you can easily change your image to toy, 3d, ps2 filter, emoji in seconds. It is simple to use, just upload your image and describe what your image will be (a short prompt), Face To Many will generate image for you. Face To Many offers high quality for its images, and you can download it for free once you generate it!

Face to Many is an AI-powered face art creation tool that allows users to transform their face images into various styles, including 3D, emoji, pixel art, video game style, claymation, or toy style. Users can simply upload a single photo and select the desired style, and the tool will automatically generate the transformed image. Face to Many also offers advanced options for users to customize their creations, such as denoising strength, prompt strength, depth control strength, and InstantID strength.

ExcelMaster is an AI-powered Excel formula and VBA assistant that provides human-level expertise. It can generate formulas, fix or explain existing formulas, learn formula skills, and draft and refine VBA scripts. ExcelMaster is the first of its kind product that handles real-world Excel structure and solves complicated formula/VBA assignments. It is far better than other “toy” formula bots, Copilot, and ChatGPT.

TorchRL is an open-source Reinforcement Learning (RL) library for PyTorch. It provides pytorch and **python-first** , low and high level abstractions for RL that are intended to be **efficient** , **modular** , **documented** and properly **tested**. The code is aimed at supporting research in RL. Most of it is written in python in a highly modular way, such that researchers can easily swap components, transform them or write new ones with little effort.

This repository is a collection of papers focused on understanding the internal mechanism of large language models (LLM). It includes research on topics such as how LLMs handle multilingualism, learn in-context, and handle factual associations. The repository aims to provide insights into the inner workings of transformer-based language models through a curated list of papers and surveys.

This repository is a collection of resources focused on interpretability in large language models (LLMs). It aims to help beginners get started in the area and keep researchers updated on the latest progress. It includes libraries, blogs, tutorials, forums, tools, programs, papers, and more related to interpretability in LLMs.

imodelsX is a Scikit-learn friendly library that provides tools for explaining, predicting, and steering text models/data. It also includes a collection of utilities for getting started with text data. **Explainable modeling/steering** | Model | Reference | Output | Description | |---|---|---|---| | Tree-Prompt | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/tree_prompt) | Explanation + Steering | Generates a tree of prompts to steer an LLM (_Official_) | | iPrompt | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/iprompt) | Explanation + Steering | Generates a prompt that explains patterns in data (_Official_) | | AutoPrompt | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/autoprompt) | Explanation + Steering | Find a natural-language prompt using input-gradients (⌛ In progress)| | D3 | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/d3) | Explanation | Explain the difference between two distributions | | SASC | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/sasc) | Explanation | Explain a black-box text module using an LLM (_Official_) | | Aug-Linear | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/aug_linear) | Linear model | Fit better linear model using an LLM to extract embeddings (_Official_) | | Aug-Tree | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/aug_tree) | Decision tree | Fit better decision tree using an LLM to expand features (_Official_) | **General utilities** | Model | Reference | |---|---| | LLM wrapper| [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/llm) | Easily call different LLMs | | | Dataset wrapper| [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/data) | Download minimially processed huggingface datasets | | | Bag of Ngrams | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/bag_of_ngrams) | Learn a linear model of ngrams | | | Linear Finetune | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/linear_finetune) | Finetune a single linear layer on top of LLM embeddings | | **Related work** * [imodels package](https://github.com/microsoft/interpretml/tree/main/imodels) (JOSS 2021) - interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compatible). * [Adaptive wavelet distillation](https://arxiv.org/abs/2111.06185) (NeurIPS 2021) - distilling a neural network into a concise wavelet model * [Transformation importance](https://arxiv.org/abs/1912.04938) (ICLR 2020 workshop) - using simple reparameterizations, allows for calculating disentangled importances to transformations of the input (e.g. assigning importances to different frequencies) * [Hierarchical interpretations](https://arxiv.org/abs/1807.03343) (ICLR 2019) - extends CD to CNNs / arbitrary DNNs, and aggregates explanations into a hierarchy * [Interpretation regularization](https://arxiv.org/abs/2006.14340) (ICML 2020) - penalizes CD / ACD scores during training to make models generalize better * [PDR interpretability framework](https://www.pnas.org/doi/10.1073/pnas.1814225116) (PNAS 2019) - an overarching framewwork for guiding and framing interpretable machine learning

xFinder is a model specifically designed for key answer extraction from large language models (LLMs). It addresses the challenges of unreliable evaluation methods by optimizing the key answer extraction module. The model achieves high accuracy and robustness compared to existing frameworks, enhancing the reliability of LLM evaluation. It includes a specialized dataset, the Key Answer Finder (KAF) dataset, for effective training and evaluation. xFinder is suitable for researchers and developers working with LLMs to improve answer extraction accuracy.

This is the official repository for 'Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing'. Magpie is a tool designed to synthesize high-quality instruction data at scale by extracting it directly from an aligned Large Language Models (LLMs). It aims to democratize AI by generating large-scale alignment data and enhancing the transparency of model alignment processes. Magpie has been tested on various model families and can be used to fine-tune models for improved performance on alignment benchmarks such as AlpacaEval, ArenaHard, and WildBench.

AI4Animation is a comprehensive framework for data-driven character animation, including data processing, neural network training, and runtime control, developed in Unity3D/PyTorch. It explores deep learning opportunities for character animation, covering biped and quadruped locomotion, character-scene interactions, sports and fighting games, and embodied avatar motions in AR/VR. The research focuses on generative frameworks, codebook matching, periodic autoencoders, animation layering, local motion phases, and neural state machines for character control and animation.

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.

Here we will keep track of the AI Game Development Tools, including LLM, Agent, Code, Writer, Image, Texture, Shader, 3D Model, Animation, Video, Audio, Music, Singing Voice and Analytics. 🔥 * Tool (AI LLM) * Game (Agent) * Code * Framework * Writer * Image * Texture * Shader * 3D Model * Avatar * Animation * Video * Audio * Music * Singing Voice * Speech * Analytics * Video Tool

Langroid is a Python framework that makes it easy to build LLM-powered applications. It uses a multi-agent paradigm inspired by the Actor Framework, where you set up Agents, equip them with optional components (LLM, vector-store and tools/functions), assign them tasks, and have them collaboratively solve a problem by exchanging messages. Langroid is a fresh take on LLM app-development, where considerable thought has gone into simplifying the developer experience; it does not use Langchain.

Awesome-Segment-Anything is a powerful tool for segmenting and extracting information from various types of data. It provides a user-friendly interface to easily define segmentation rules and apply them to text, images, and other data formats. The tool supports both supervised and unsupervised segmentation methods, allowing users to customize the segmentation process based on their specific needs. With its versatile functionality and intuitive design, Awesome-Segment-Anything is ideal for data analysts, researchers, content creators, and anyone looking to efficiently extract valuable insights from complex datasets.

ClearML Serving is a command line utility for model deployment and orchestration, enabling model deployment including serving and preprocessing code to a Kubernetes cluster or custom container based solution. It supports machine learning models like Scikit Learn, XGBoost, LightGBM, and deep learning models like TensorFlow, PyTorch, ONNX. It provides a customizable RestAPI for serving, online model deployment, scalable solutions, multi-model per container, automatic deployment, canary A/B deployment, model monitoring, usage metric reporting, metric dashboard, and model performance metrics. ClearML Serving is modular, scalable, flexible, customizable, and open source.

The 'gritlm' repository provides all materials for the paper Generative Representational Instruction Tuning. It includes code for inference, training, evaluation, and known issues related to the GritLM model. The repository also offers models for embedding and generation tasks, along with instructions on how to train and evaluate the models. Additionally, it contains visualizations, acknowledgements, and a citation for referencing the work.

Raspberry is an open source project aimed at creating a toy dataset for finetuning Large Language Models (LLMs) with reasoning abilities. The project involves synthesizing complex user queries across various domains, generating CoT and Self-Critique data, cleaning and rectifying samples, finetuning an LLM with the dataset, and seeking funding for scalability. The ultimate goal is to develop a dataset that challenges models with tasks requiring math, coding, logic, reasoning, and planning skills, spanning different sectors like medicine, science, and software development.

This repository provides an implementation of QA-MDT, integrating state-of-the-art models for music generation. It offers a Quality-Aware Masked Diffusion Transformer for enhanced music generation. The code is based on various repositories like AudioLDM, PixArt-alpha, MDT, AudioMAE, and Open-Sora. The implementation allows for training and fine-tuning the model with different strategies and datasets. The repository also includes instructions for preparing datasets in LMDB format and provides a script for creating a toy LMDB dataset. The model can be used for music generation tasks, with a focus on quality injection to enhance the musicality of generated music.

SolarLLM Chat Demo is a repository showcasing a chat demo using Streamlit and Gradio. It provides a visual demonstration of chat functionality using these tools. For more detailed usage examples, users can refer to the SolarLLM Cookbook available at the provided GitHub link.

Starmoon is an affordable, compact AI-enabled device that can understand and respond to your emotions with empathy. It offers supportive conversations and personalized learning assistance. The device is cost-effective, voice-enabled, open-source, compact, and aims to reduce screen time. Users can assemble the device themselves using off-the-shelf components and deploy it locally for data privacy. Starmoon integrates various APIs for AI language models, speech-to-text, text-to-speech, and emotion intelligence. The hardware setup involves components like ESP32S3, microphone, amplifier, speaker, LED light, and button, along with software setup instructions for developers. The project also includes a web app, backend API, and background task dashboard for monitoring and management.

Imagine a world of beautifully photographed toys!

Generates unique toy car concepts in various styles and settings.

I make modular Sci-Fi toy ship concepts.

Who let the dogs out? Who stole your favorite toy? Who moved my cheese? Let’s find out!

Ask it anything and learn the future. A highly advanced artificial intelligence trapped inside a classic Magic 8-Ball toy for you to enjoy. Can this actually tell you the future of your fortune? Concentrate and ask again!

Create your own awesome brick mini figures

Transforms ideas into Lego creations, keeps creation details private.

🎄 Santa's village, holiday tools and toys 🎁

为所有人创造潮玩

Expert on AI-enhanced sex dolls, providing informative insights and product recommendations.

Dream your own LEGO set.

Tech ideas inspirer for fun pet entertainment

The best board games just for you!

I create 3D doll head models from photos or descriptions.

Transform your child's stuffed animals into interactive, talking playmates with distinct personalities, enhancing children's play and emotional growth.

Designs cute, household item-themed creatures.

A concise image generation expert for minifigures.

Interprets cat photos to narrate humorous, thoughtful cat perspectives.

A playful designer bringing kids' potty humor to life in a fun, imaginative way.

A friendly companion for those afraid of the dark.