Butternut AI provides machine-learning models, research, training resources, or evaluation tools.
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Fast open framework for deep learning.
Cal.ai provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Torch-like deep learning framework for Javascript with support for tensors, autograd, optimizers, and other neural net constructs.
Interactive Hugging Face app that shares a machine-learning model, framework, demonstration or technical resource.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Chain of Thought provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Charisma provides machine-learning models, research, training resources, or evaluation tools.
ChatGPT, DALL-E 2 and the collapse of the creative process provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
A PyTorch based deep learning library for drug pair scoring.
ChessArena provides machine-learning models, research, training resources, or evaluation tools.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Implementation of Random Forest in Common Lisp.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Python library for data-centric AI and machine learning with messy, real-world data and labels.
Optimization library focused on machine learning, pythonic implementations of gradient descent, LBFGS, rmsprop, adadelta and others.
CLIP Interrogator supports machine learning models, deployment, inspection, datasets, or AI development workflows.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.