A high-throughput and memory-efficient inference and serving engine for LLMs
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Updated
Oct 31, 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: Deep Learning for Chemical Image Recognition using Efficient-Net V2 + Transformer
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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