Tensors and Dynamic neural networks in Python with strong GPU acceleration
每个推荐都保留与其仓库、审计和安装路径的明确关联。
搜索结果: gpu-training
英文目录🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Unsloth Studio is a web UI for training and running open models like Gemma 4, Qwen3.6, DeepSeek, gpt-oss locally.
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Reviews animation and motion code against a high craft bar derived from Emil Kowalski's design engineering philosophy. Default to flagging; approval is earned.
Multi-lingual large voice generation model, providing inference, training and deployment full-stack ability.
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
A WebGL accelerated JavaScript library for training and deploying ML models.
cuDF - GPU DataFrame Library
Deeplake is AI Data Runtime for Agents. It provides serverless postgres with a multimodal datalake, enabling scalable retrieval and training.
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.