Model training and deployment

SRM is a spatial reasoning framework based on denoising generative models for processing reasoning tasks on sets of continuous variables. It progressively infers a continuous representation of each unobserved variable by assigning independent noise levels to these variables. This technology performs well when dealing with complex distributions and can effectively reduce hallucinations during the generation process. SRM demonstrated for the first time that a denoising network can predict the generation order, significantly improving the accuracy of a specific inference task. The model was developed by the Max Planck Institute for Informatics in Germany and aims to promote research on spatial reasoning and generative models.

One Shot LoRA is an online platform focused on quickly training LoRA models from videos. It uses advanced machine learning technology to efficiently convert video content into LoRA models, providing users with fast and convenient model generation services. The main advantages of this product are its simplicity, no need to log in, and secure privacy. It does not require users to upload private data, nor does it store or collect any user information, ensuring the privacy and security of user data. This product is mainly aimed at users who need to quickly generate LoRA models, such as designers, developers, etc., to help them quickly obtain the required model resources and improve work efficiency.

Sparsh is a family of general-purpose tactile representations trained with self-supervised algorithms such as MAE, DINO and JEPA. It can generate useful representations for DIGIT, Gelsight'17 and Gelsight Mini, and significantly surpass the end-to-end model in the downstream tasks proposed by TacBench. It can also provide support for data-efficient training of new downstream tasks. The Sparsh project contains PyTorch implementations, pretrained models, and datasets released with Sparsh.

D-FINE is a powerful real-time object detection model that achieves excellent performance without adding additional inference and training costs by redefining the bounding box regression task in DETRs as fine-grained distribution refinement (FDR) and introducing global optimal localization self-distillation (GO-LSD). The model was developed by researchers at the Chinese Academy of Sciences to improve the accuracy and efficiency of target detection.

In-Context LoRA is a fine-tuning technique for diffusion transformers (DiTs) that enables fine-tuning for specific tasks while remaining task-independent by incorporating images instead of just text. The main advantage of this technique is the ability to perform efficient fine-tuning on small data sets without requiring any modifications to the original DiT model, just changing the training data. In-Context LoRA generates high-fidelity image collections that better match prompt requirements by jointly describing multiple images and applying task-specific LoRA fine-tuning. This technique is of great significance to the field of image generation as it provides a powerful tool to generate high-quality images for specific tasks without sacrificing task independence.

LibreFLUX is an open source version based on the Apache 2.0 license that provides the full T5 context length, uses attention masks, restores classifier free guidance, and removes most of the FLUX aesthetic fine-tuning/DPO. This means it's less aesthetically pleasing than base FLUX, but has the potential to be more easily fine-tuned to any new distribution. LibreFLUX was developed with the core principles of open source software in mind, namely that it is difficult to use, slower and more clunky than proprietary solutions, and has an aesthetic stuck in the early 2000s.

Stability AI is a company focused on generative artificial intelligence technology, providing a variety of AI models, including text to image, video, audio, 3D and language models. These models are capable of processing complex cues and producing realistic images and videos, as well as high-quality music and sound effects. The company offers flexible licensing options, including self-hosted licenses and platform APIs, to meet the needs of different users. Stability AI is committed to providing high-quality AI services to everyone around the world through open models.

4M is a framework for training multi-modal and multi-task models, capable of handling a variety of visual tasks and capable of multi-modal condition generation. The model demonstrates its versatility and scalability on visual tasks through experimental analysis, laying the foundation for further exploration of multi-modal learning in vision and other fields.

AIToolBox focuses on providing customized AI solutions and Swiss hosting services to enterprises to help them control data and analysis. Our custom AI tools are designed to ensure data privacy, operational efficiency and strategic decision-making. With AIToolBox, you can leverage the power of AI to drive strategic decisions and improve operational efficiency. Contact [email protected] to inquire about business cooperation.

Cleora PRO is a tool that helps data science teams create high-quality customer and product embedding vectors without expensive hardware. It can represent entities (such as customers, products, stores, accounts, etc.) through embedded vectors, similar to Word2Vec or BERT in text, or CLIP in images. Cleora's embedding vectors are behavioral, represented by an entity's behavioral history, which exists in the form of a large graph. Using Cleora PRO, you can build enterprise models such as recommendation systems, customer segmentation, propensity prediction, lifetime value modeling, churn prediction, and more.

Controlling Text-to-Image Diffusion investigates how to effectively guide or control powerful text-to-image generation models for a variety of downstream tasks. The orthogonal fine-tuning (OFT) method is proposed, which can maintain the generative ability of the model. OFT can keep the hyperspherical energy between neurons unchanged and prevent model collapse. The authors consider two important fine-tuning tasks: agent-driven generation and controlled generation. The results show that the OFT method is superior to existing methods in terms of generation quality and convergence speed.

AuroraAI is a product developed by Incribo that generates safe and high-quality training data to accelerate the development of your AI models. It can be used for a variety of purposes, including speech synthesis, audio segmentation, character modeling, landscape design, image processing, etc. AuroraAI focuses on privacy protection, is cost-effective, supports multi-modal data generation, and has unlimited possibilities for change. Users have data ownership and can use it directly. Currently in early access, welcome to join our community.

V7 is an AI data engine that provides a complete infrastructure for enterprise-level training data, covering annotation, workflow, datasets and human-in-the-loop. It can help users label, process and manage training data quickly and efficiently, improving the accuracy and performance of AI models. V7 supports automated annotation, video annotation, document processing and other functions, and is suitable for various industries and application scenarios.

Keras is an API designed for humans, following best practices, simplifying cognitive load, providing a consistent and simple API, minimizing the number of user actions required for common use cases, and providing clear and actionable error messages. Keras is designed to give an unfair advantage to any developer looking to roll out machine learning-based applications. Keras focuses on debugging speed, code elegance and simplicity, maintainability, and deployability. With Keras, your codebase is smaller, more readable, and easier to iterate on. Your models run faster with XLA compilation and Autograph optimization, and are easier to deploy on every platform (server, mobile, browser, embedded).

TFLearn is a deep learning library based on TensorFlow that provides a high-level API for implementing deep neural networks. It features a high-level API that is easy to use and understand, rapid prototyping capabilities, comprehensive TensorFlow transparency, and supports the latest deep learning technologies. TFLearn supports convolutional network, LSTM, bidirectional RNN, batch normalization, PReLU, residual network, generation network and other models. It can be used for tasks such as image classification and sequence generation.

MindSpore is Huawei's open-source and self-developed AI framework that supports deep learning training and inference in all scenarios of the device, edge, and cloud, and is applied in AI fields such as computer vision and natural language processing. It has functions such as general automatic differentiation based on source code conversion, automatic implementation of distributed parallel training, data processing and graph execution engine. The framework is open source and suitable for data scientists and algorithm engineers.

Heimdall is an automated machine learning tool that can quickly build customized production model endpoints to help users build machine learning experiences. Heimdall seamlessly embeds machine learning into your organization, enabling you to build, analyze, and deploy machine learning models in less than 10 minutes. Once you build your model, you can enable it as an API endpoint to power your predictive insights!

The Local AI Playground is a local AI management, verification and inference tool that enables AI experiments in an offline environment without the need for a GPU. This product is a native application designed to simplify the entire process. It is free and open source.

Cerebrium is a machine learning framework that makes it easy to train, deploy, and monitor machine learning models with just a few lines of code. We run everything on serverless CPU/GPU and only charge based on usage. You can deploy models from libraries such as Pytorch, Huggingface, Tensorflow, and more.

Meteron AI is an all-in-one AI toolset that can handle load balancing, sorting, storage, and limiting of AI systems. It helps developers get rid of time-consuming and unnecessary processes, allowing teams to focus on creating better models and getting more traffic. Meteron AI provides elastic queues, unlimited storage, per-user billing, and works with any model. Pricing plans include Free, Pro and Enterprise.

syntheticAIdata is a platform that quickly generates large-scale synthetic datasets for training visual AI models. By using syntheticAIdata, you can easily generate large synthetic datasets to significantly speed up visual AI model training for tasks such as image classification, image segmentation, and object detection. Our solutions will help you bring AI-based applications to market faster. syntheticAIdata is supported by Microsoft for Startups and is part of the NVIDIA Inception program.

Local AI Playground is a desktop client application for local AI model management, verification and inference. It provides an AI experimental environment with zero technical setup and does not require GPU support. Users can run AI models in a local offline environment and enjoy higher privacy protection. The application has a simple and easy-to-use interface and powerful functions, supporting functions such as CPU inference, model download and management, and model integrity verification. The local AI playground is free and open source.

GPUX is a platform for quickly running cloud GPUs. It provides high-performance GPU instances for running machine learning workloads. GPUX supports a variety of common machine learning tasks, including stable diffusion, Blender, Jupyter Notebook, etc. It also provides functions such as stable diffusion SDXL0.9, Alpaca, LLM and Whisper. GPUX also has advantages such as 1 second cold start time, Shared Instance Storage and ReBar+P2P support. The pricing is reasonable and it is positioned as a cloud platform that provides high-performance GPU instances.

Graphite Note is the world’s easiest-to-use, no-code machine learning platform. It helps users generate business insights and forecasts in minutes without coding. Through Graphite Note, users can use various machine learning models for data analysis, prediction, and decision support. The platform provides an intuitive interface and easy-to-use tools that enable users to quickly build and train models and turn results into practical business insights. Graphite Note also provides a wealth of functions, including data visualization, feature engineering, model evaluation and optimization, etc., to help users fully utilize the potential of machine learning. The platform also supports multiple data sources and formats, giving users the flexibility to process and analyze various types of data. Graphite Note's pricing is flexible and reasonable, suitable for individual users, small teams, and enterprise customers. Whether you are a data scientist, business analyst or decision maker, Graphite Note is ideal for achieving business insights and predictions.

Liner.ai is a free tool that lets you build and deploy machine learning applications in minutes, without coding or machine learning expertise. It uses your training data and provides an easy-to-integrate machine learning model.

Lobe is a free, easy-to-use tool that helps you train custom machine learning models and use them in your applications. Lobe has everything you need to implement your machine learning ideas. Just show it the example you want it to learn and it will automatically train a custom machine learning model that can be used in your application.

DirectAI is a platform based on large language models and zero-shot learning that can instantly build a model that suits your needs based on your description, without the need for training data. You can deploy and iterate models in seconds, eliminating the time and expense of assembling training data, labeling data, training the model, and fine-tuning the model. Headquartered in New York City and backed by venture capital, DirectAI is changing the way people use artificial intelligence in the real world.

Hasty is a one-stop visual AI platform that provides tools for everything from raw images and videos to production-ready models. No MLops skills or complex integrations required for all your visual AI needs. Hasty uses AI training methods to accelerate the data annotation process through automated annotation, intelligent quality control and other functions. It also provides 90% automated quality control work, reducing complex review processes and redundant work. Hasty is suitable for various scenarios, including image processing, video analysis, model training, etc.

Roboflow is a comprehensive platform for building and deploying computer vision models. It is used by over 250,000 engineers to create datasets, train models, and deploy to production. Roboflow enables you to train a working state-of-the-art computer vision model in less than 24 hours with just a few dozen example images. It provides a series of functions such as data set management, annotation tools, model training, and model deployment, and supports integration with various environments and tools.