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Section: Frameworks for Training · Minimalist ML framework for Rust .
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Candle is a minimalist ML framework for Rust with a focus on performance (including GPU support) and ease of use. Try our online demos: whisper, LLaMA2, T5, yolo, Segment Anything.
Section: Frameworks for Training · Minimalist ML framework for Rust .
Section: Rust · Candle is a minimalist ML framework for Rust with a focus on performance (including GPU support) and ease of use.
Section: 1. Core Frameworks & Libraries · Minimalist ML framework for Rust. PyTorch-like API with focus on performance and simplicity.
Section: Projects · Candle is a minimalist ML framework for Rust with a focus on performance (including GPU support) and ease of use. Try our online demos: whisper, LLaMA2, T5, yolo, Segment Anything.
Section: Artificial Intelligence · [candle-core] - a minimalist ML framework with a focus on easiness of use and on performance (including GPU support)
How to use the Hexagon Delegate to speed up model inference on mobile and edge devices. Also see blog post Accelerating TensorFlow Lite on Qualcomm Hexagon DSPs.
(label: good first issue) PyTorch is an open source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing.
Python module for building complex pipelines of batch jobs. Handles dependency resolution, workflow management, visualization, and Hadoop integration. Built at Spotify and battle-tested in production. Apache 2.0 licensed.
(formerly known as pytorch-transformers and pytorch-pretrained-bert) provides state-of-the-art general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet, CTRL...) for Natural Language Understanding (NLU) and Natural Language Generation (NLG) with over 32+ pretrained models in…
(from Hpcaitech) - A Unified Deep Learning System for Large-Scale Parallel Training (1D, 2D, 2.5D, 3D and sequence parallelism, and ZeRO protocol).
"Use airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command line utilities make performing complex surgeries on DAGs a snap. The rich user interface makes it…