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Karpathy's microGPT

Cerebras Systems provides open-source GPT models optimized for their AI-specific hardware. While designed for large-scale deployment, Cerebras-GPT models can also be run on specific compatible local setups, making it suitable for research or enterprise applications.

Open-source machine learning framework by Google.

Revolutionary AI for protein structure prediction

DeepfakeVFX.com is a comprehensive platform focused on deepfake technology. It offers extensive resources for both beginners and advanced users, including tutorials and guides on creating deepfakes us

Train, optimize models, deploy AI apps, leverage APIs for cost-effective development.

An open-source framework accelerating research prototyping to production deployment.

Open standard for machine learning model interoperability.

Cradle, a leading platform in protein engineering, revolutionizes protein design using sophisticated machine learning. By streamlining the design process, it enables researchers to create proteins wit

Train, optimize, access libraries, and track ML models with real-time monitoring.

Genesis Therapeutics is a biotech leader in molecular AI that unites deep learning and physics-based machine learning in its proprietary GEMS platform and Pearl foundation model to unlock tough protei

Build, deploy, & optimize AI apps with pre-trained models, algorithms, and real-time analytics.

Build and deploy deep learning models, create architectures from scratch or use pre-trained models, experiment without coding.

Accelerate training, optimize models, and deploy quickly to target hardware without AI hardware dependency.

The Microsoft Cognitive Toolkit (CNTK) is an open-source deep learning toolkit developed by Microsoft. It allows users to efficiently train deep learning models with flexible architecture and scalabil

ggml is a machine learning tensor library written in C that provides high performance and large model support on commodity hardware. The library supports 16-bit floats, integer quantization, automatic

CEBRA is a library designed to estimate Consistent EmBeddings of high-dimensional Recordings utilizing Auxiliary variables. By leveraging self-supervised learning algorithms implemented with PyTorch,