# \[ANN\] PyTorch bindings

**URL:** <https://discuss.ocaml.org/t/ann-pytorch-bindings/3049>\
**Category:** Community\
**Tags:** announce\
**Created:** [December 13, 2018, 8:44pm UTC](https://discuss.ocaml.org/t/ann-pytorch-bindings/3049 "2018-12-13T20:44:47Z")\
**Posts on this page:** 1\
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**Author:** ![laurent](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ocaml.org/laurent/32/734_2.png) [@laurent](https://discuss.ocaml.org/u/laurent)\
**Post date:** [December 13, 2018, 8:44pm UTC](https://discuss.ocaml.org/t/ann-pytorch-bindings/3049/1 "2018-12-13T20:44:47Z")

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We are very pleased to announce the first release of our PyTorch bindings for ocaml. These bindings provide a NumPy like tensor library with GPU acceleration and support for automatic differentiation.

The `torch` package can be installed via opam. More details can be found in the [github repo](https://github.com/LaurentMazare/ocaml-torch), including a [tutorial](https://github.com/LaurentMazare/ocaml-torch/tree/master/examples/mnist) training some neural networks on the MNIST dataset, various deep-learning examples: Generative Adverserial Networks, Neural Style Transfer, state of the art computer vision models on CIFAR-10, etc. Pre-trained weights for some recent computer vision models are also provided.

Any feedback is very welcome. Hopefully we will write a couple new tutorials to describe the current examples and add more examples in the next few weeks.

(note that the `tensorflow` package providing TensorFlow bindings also has been updated this week and is now up to speed with the github repo)

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