mni-ml / framework
A machine learning library with a TypeScript API and Rust backend. CUDA and WebGPU compatibility. Built to understand how ML frameworks and models work internally.
Why this job: says: machine learning library; topics: machine-learning
What it does
- Automatic differentiation. full backward pass through an autograd tape
- GPU acceleration. CUDA (NVIDIA) and WebGPU (Metal/Vulkan/DX12) backends
- PyTorch-like API. familiar Tensor, Module, Parameter, optimizer classes
- Comprehensive ops. elementwise, matmul, conv1d/conv2d, pooling, reductions, activations
- Built-in modules. Linear, Conv1d, Conv2d, Embedding, ReLU, Sigmoid, Tanh
Get started
npm install @mni-ml/framework - Maintenance
- Inactive
- Last commit 6 months ago
- Stars
- 1,021
- On GitHub
- Licence
- MIT
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- None yet
- No releases
- Built with
- Rust
- 48% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 33% closed
- 2 still open
- Pull requests
- 34 merged
- 3 waiting
- Releases
- None
- Never published
- No contributing guide
- No security policy
- No code of conduct
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More: languages, topics and project record
Languages
- Rust 48%
- TypeScript 40%
- Cuda 6%
- WGSL 5%
Topics
- machine-learning
- pytorch-implementation
- webgpu
- cuda
- cuda-kernels
- rust
Project record
- JobAI libraries and models
- StatusListed
- Commits319
- Forks130
- Watching7
- Stars in 28 days+5
- CreatedJan 8, 2026
- First seen by usNov 7, 2026
- CheckedNov 8, 2026