From 58d9138506507f646c8900624552fe4d2a5a3e6c Mon Sep 17 00:00:00 2001 From: Konstantin Gulin <66528950+KSGulin@users.noreply.github.com> Date: Thu, 25 May 2023 17:56:10 +0100 Subject: [PATCH] IC doc fixes (#1577) --- integrations/torchvision/README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/integrations/torchvision/README.md b/integrations/torchvision/README.md index 241a7a8ff03..19fcf181c7a 100644 --- a/integrations/torchvision/README.md +++ b/integrations/torchvision/README.md @@ -46,7 +46,7 @@ pip install sparseml[torchvision] Neural Magic has pre-sparsified versions of common Torchvision models such as ResNet-50. These models can be deployed directly or can be fine-tuned onto custom dataset via sparse transfer learning. This makes it easy to create a sparse image classification model trained on your dataset. -[Check out the available models](https://sparsezoo.neuralmagic.com/?domain=cv&sub_domain=classification&page=1) +[Check out the available models](https://sparsezoo.neuralmagic.com/?useCase=classification) ### Recipes @@ -104,7 +104,7 @@ sparseml.image_classification.train \ For full usage, run: ```bash -sparseml.image_classification --help +sparseml.image_classification.train --help ``` ## Quick Start: Sparse Transfer Learning with the CLI @@ -113,7 +113,7 @@ sparseml.image_classification --help Sparse Transfer is quite similiar to the typical transfer learning process used to train image classification models, where we fine-tune a checkpoint pretrained on ImageNet onto a smaller downstream dataset. With Sparse Transfer Learning, we simply start the fine-tuning process from a pre-sparsified checkpoint and maintain sparsity while the training process occurs. -In this example, we will fine-tune a 95% pruned version of ResNet-50 ([available in SparseZoo](https://sparsezoo.neuralmagic.com/models/cv%2Fclassification%2Fresnet_v1-50%2Fpytorch%2Fsparseml%2Fimagenet%2Fpruned95_quant-none)) onto ImageNette. +In this example, we will fine-tune a 95% pruned version of ResNet-50 ([available in SparseZoo](https://sparsezoo.neuralmagic.com/models/resnet_v1-50-imagenet-pruned95_quantized?comparison=resnet_v1-50-imagenet-base)) onto ImageNette. ### Kick off Training