Examples of programs built using Modal
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Updated
May 20, 2024 - Python
Examples of programs built using Modal
Tensors and Dynamic neural networks in Python with strong GPU acceleration
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Exascale multiphase flow simulation
Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators.
『ゼロから作る Deep Learning ❸』(O'Reilly Japan, 2020)
Pytorch domain library for recommendation systems
Spectral, quasi-3D Particle-In-Cell code, for CPU and GPU
cuML - RAPIDS Machine Learning Library
Accelerate local LLM inference and finetuning (LLaMA, Mistral, ChatGLM, Qwen, Baichuan, Mixtral, Gemma, etc.) on Intel CPU and GPU (e.g., local PC with iGPU, discrete GPU such as Arc, Flex and Max). A PyTorch LLM library that seamlessly integrates with llama.cpp, Ollama, HuggingFace, LangChain, LlamaIndex, DeepSpeed, vLLM, FastChat, etc.
Aer is a high performance simulator for quantum circuits that includes noise models
(GPU accelerated) Multi-arch (linux/amd64, linux/arm64/v8) JupyterLab R docker images. Please submit Pull Requests to the GitLab repository. Mirror of
Example of image export from MRTech IFF SDK
[WOLF] Vulkan Accelerated Render of GLTF - a fresnel based renderer
A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.
Open3D: A Modern Library for 3D Data Processing
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