nobuco
coremltools
| nobuco | coremltools | |
|---|---|---|
| 1 | 12 | |
| 192 | 4,076 | |
| - | 1.6% | |
| 8.7 | 8.7 | |
| 16 days ago | 10 days ago | |
| Python | Python | |
| MIT License | BSD 3-clause "New" or "Revised" License |
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nobuco
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Introducing Nobuco: PyTorch to Tensorflow converter. Intuitive, flexible, efficient.
Hence, [Nobuco](https://github.com/AlexanderLutsenko/nobuco). It's designed with simplicity and hackability in mind and automatically solves mismatching channel orders offering near-optimal performance. Try it, and spread the word if you like it. If not, feel free to open an issue or feature request. Any forms of contribution are highly welcome!
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.
What are some alternatives?
exporters - Export Hugging Face models to Core ML and TensorFlow Lite
RobustVideoMatting - Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX, CoreML!
PINTO_model_zoo - A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
efficientnet-lite-keras - Keras reimplementation of EfficientNet Lite.
tensorflow_macos - TensorFlow for macOS 11.0+ accelerated using Apple's ML Compute framework.
d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
3d-model-convert-to-gltf - Convert 3d model (STL/IGES/STEP/OBJ/FBX) to gltf and compression
ftc_ladel - A TFLite+YoloV7 enabled labeling and training pipeline
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.
best-of-ml-python - 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
password-manager-resources - A place for creators and users of password managers to collaborate on resources to make password management better.