coremltools
swift-coreml-transformers
| coremltools | swift-coreml-transformers | |
|---|---|---|
| 12 | 4 | |
| 4,131 | 1,588 | |
| 1.6% | 0.1% | |
| 8.5 | 2.7 | |
| 18 days ago | 6 months ago | |
| Python | Swift | |
| BSD 3-clause "New" or "Revised" License | Apache License 2.0 |
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coremltools
- CoreML commit from Apple mentions iOS17 exclusive features
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Lisa Su Saved AMD. Now She Wants Nvidia's AI Crown
Instead of trying to integrate the whole stack of, say, pytorch, Apple's primary approach has been converting models to work with Apple's stack.
https://github.com/apple/coremltools
Clearly no one is going to be doing training or even fine tuning on Apple hardware at any scale (it competes at the low end, but at scale you invariably will be using nvidia hardware), but once you have a decent model it's a robust way of using it on Apple devices.
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Stable Diffusion for M1 iPad
There is one guy who was able to run it on iOS. See this thread for more information. Basically, the idea is to convert torch models to CoreMl. Only the CLIP tokenizer's implementation is currently missing. I guess this guy will keep modifications private, but he is trying to optimize model for lower RAM requirements.
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MacBook Pro 14” M1 Pro (worth buying for programming)
Afaik (correct me if I’m wrong) both PyTorch and tensorflow only use the gpu when training and not the neural engine. I think the neural engines can be used for inference if the model is in the CoreML format (https://github.com/apple/coremltools)
- Is it possible to convert a yolov5 model to a CoreML/.mlmodel to work in an IOS app?
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ML model conversion
CoreML Tools
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Supreme Court, in a 6–2 ruling in Google v. Oracle, concludes that Google’s use of Java API was a fair use of that material
And Python.
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Apple’s New M1 Chip is a Machine Learning Beast
There's literally an Apple provided tool, called [coremltools[(https://github.com/apple/coremltools) to convert many common PyTorch and TensorFlow models to CoreML.
swift-coreml-transformers
- Swift Core ML 3 implementations of GPT-2, DistilGPT-2, BERT, and DistilBERT
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Stable Diffusion for M1 iPad
There is one guy who was able to run it on iOS. See this thread for more information. Basically, the idea is to convert torch models to CoreMl. Only the CLIP tokenizer's implementation is currently missing. I guess this guy will keep modifications private, but he is trying to optimize model for lower RAM requirements.
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AI in XCode/Swift?
Hugging Face, which does a lot of the python said of machine learning stuff, also has this repository: https://github.com/huggingface/swift-coreml-transformers however this is 3 years old at this point. This serves as perhaps a more complete example of stuff you need to do to get good NLP stuff in Xcode/Swift. This repository includes examples of converting PyTorch trained models over to CoreML models that play nice with iOS development.
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How do I load my app faster?
Looking at this page, you probably want to install HuggingFace with the CPU-only options (pip install transformers[torch]) or from their mobile-friendly repo instead.
What are some alternatives?
RobustVideoMatting - Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX, CoreML!
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
tensorflow_macos - TensorFlow for macOS 11.0+ accelerated using Apple's ML Compute framework.
3d-model-convert-to-gltf - Convert 3d model (STL/IGES/STEP/OBJ/FBX) to gltf and compression
MMdnn - MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
password-manager-resources - A place for creators and users of password managers to collaborate on resources to make password management better.
hummingbird - Hummingbird compiles trained ML models into tensor computation for faster inference.
foundationdb - FoundationDB - the open source, distributed, transactional key-value store
GmsCore - Free implementation of Play Services
docker - Docker - the open-source application container engine
uprove-javascript-sdk - The U-Prove JavaScript SDK implements the client-side of the U-Prove Cryptographic Specification, and is a companion to the U-Prove C# SDK. It can be used to write web clients interacting with U-Prove services. For more information about the U-Prove technology, please visit http://www.microsoft.com/uprove.
OpenCL-examples - Simple OpenCL examples for exploiting GPU computing