From 6c3a46cc8b89bcc275a87f2807a533b49f817fcb Mon Sep 17 00:00:00 2001 From: Alexander Borzunov Date: Thu, 30 Mar 2023 19:25:54 +0400 Subject: [PATCH] Fix broken link, min torch version in readme (#562) --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 139408c1e..e5f4e1587 100644 --- a/README.md +++ b/README.md @@ -36,12 +36,12 @@ feel free to submit a pull request that adds your project to this list. * **Training Transformers Together** ([webpage](https://training-transformers-together.github.io/), [code](https://github.com/learning-at-home/dalle-hivemind)) — a NeurIPS 2021 demonstration that trained a collaborative text-to-image Transformer model. * **CALM** ([webpage](https://huggingface.co/CALM), [code](https://github.com/NCAI-Research/CALM)) — a masked language model trained on a combination of Arabic datasets. * **sahajBERT** ([blog post](https://huggingface.co/blog/collaborative-training), [code](https://github.com/tanmoyio/sahajbert)) — a collaboratively pretrained ALBERT-xlarge for the Bengali language. -* **HivemindStrategy** ([docs](https://pytorch-lightning.readthedocs.io/en/latest/api/pytorch_lightning.strategies.HivemindStrategy.html)) in PyTorch Lightning allows adapting your existing pipelines to training over slow network with unreliable peers. +* **HivemindStrategy** ([docs](https://lightning.ai/docs/pytorch/stable/advanced/third_party/hivemind.html?highlight=hivemindstrategy)) for PyTorch Lightning allows adapting your existing pipelines to training over slow network with unreliable peers. ## Installation Before installing, make sure that your environment has Python 3.7+ -and [PyTorch](https://pytorch.org/get-started/locally/#start-locally) 1.6.0 or newer. They can be installed either +and [PyTorch](https://pytorch.org/get-started/locally/#start-locally) 1.9.0 or newer. They can be installed either natively or with [Anaconda](https://www.anaconda.com/products/individual). You can get [the latest release](https://pypi.org/project/hivemind) with pip or build hivemind from source.