Instructions to use LibreYOLO/LibreAlexNetb-cls with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LibreYOLO
How to use LibreYOLO/LibreAlexNetb-cls with LibreYOLO:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Download NOTICE from LibreYOLO/LibreAlexNetb-cls: direct link, hf CLI and curl.
- Browser
- Download file 760 Bytes
-
https://huggingface.co/LibreYOLO/LibreAlexNetb-cls/resolve/main/NOTICE
- Command line
-
hf download hf://LibreYOLO/LibreAlexNetb-cls/NOTICE
-
curl -L -o NOTICE https://huggingface.co/LibreYOLO/LibreAlexNetb-cls/resolve/main/NOTICE
760 Bytes
| LibreAlexNetb-cls weights | |
| ------------------------- | |
| This product contains weights released by torchvision | |
| (https://github.com/pytorch/vision) at commit 336d36e8db990a905498c73933e35231876e28bc. | |
| Official checkpoint: alexnet-owt-7be5be79.pth | |
| Copyright (c) Soumith Chintala 2016 and torchvision contributors. | |
| The checkpoint has no separate per-object license file. Redistribution uses | |
| the releasing project's BSD-3-Clause license on an explicitly disclosed | |
| implied basis; this is not a publisher-confirmed checkpoint-specific grant. | |
| Torchvision warns that pretrained-model terms may derive from training data. | |
| The ImageNet dataset and source-image terms remain the user's responsibility. | |
| Conversion only adds LibreYOLO metadata. Learned tensors are unchanged. | |