A high-throughput and memory-efficient inference and serving engine for LLMs
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Updated
Nov 21, 2024 - Python
A high-throughput and memory-efficient inference and serving engine for LLMs
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.
SkyPilot: Run AI and batch jobs on any infra (Kubernetes or 12+ clouds). Get unified execution, cost savings, and high GPU availability via a simple interface.
Fast and flexible AutoML with learning guarantees.
Everything we actually know about the Apple Neural Engine (ANE)
GPT2 for Multiple Languages, including pretrained models. GPT2 多语言支持, 15亿参数中文预训练模型
Large-scale LLM inference engine
Everything you want to know about Google Cloud TPU
Neural network-based chess engine capable of natural language commentary
Implementation of a Tensor Processing Unit for embedded systems and the IoT.
Differentiable Fluid Dynamics Package
Dual Edge TPU Adapter to use it on a system with single PCIe port on m.2 A/B/E/M slot
Free TPU for FPGA with compiler supporting Pytorch/Caffe/Darknet/NCNN. An AI processor for using Xilinx FPGA to solve image classification, detection, and segmentation problem.
JetStream is a throughput and memory optimized engine for LLM inference on XLA devices, starting with TPUs (and GPUs in future -- PRs welcome).
Julia on TPUs
DECIMER Image Transformer is a deep-learning-based tool designed for automated recognition of chemical structure images. Leveraging transformer architectures, the model converts chemical images into SMILES strings, enabling the digitization of chemical data from scanned documents, literature, and patents.
Benchmarking suite to evaluate 🤖 robotics computing performance. Vendor-neutral. ⚪Grey-box and ⚫Black-box approaches.
🖼 Training StyleGAN2 on TPUs in JAX
EfficientNet, MobileNetV3, MobileNetV2, MixNet, etc in JAX w/ Flax Linen and Objax
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