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‎CODE_OF_CONDUCT.md

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# Code of Conduct
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## Our Pledge
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In the interest of fostering an open and welcoming environment, we as
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contributors and maintainers pledge to make participation in our project and
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our community a harassment-free experience for everyone, regardless of age, body
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size, disability, ethnicity, sex characteristics, gender identity and expression,
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level of experience, education, socio-economic status, nationality, personal
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appearance, race, religion, or sexual identity and orientation.
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## Our Standards
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Examples of behavior that contributes to creating a positive environment
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include:
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* Using welcoming and inclusive language
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* Being respectful of differing viewpoints and experiences
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* Gracefully accepting constructive criticism
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* Focusing on what is best for the community
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* Showing empathy towards other community members
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Examples of unacceptable behavior by participants include:
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* The use of sexualized language or imagery and unwelcome sexual attention or
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advances
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* Trolling, insulting/derogatory comments, and personal or political attacks
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* Public or private harassment
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* Publishing others' private information, such as a physical or electronic
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address, without explicit permission
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* Other conduct which could reasonably be considered inappropriate in a
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professional setting
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## Our Responsibilities
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Project maintainers are responsible for clarifying the standards of acceptable
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behavior and are expected to take appropriate and fair corrective action in
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response to any instances of unacceptable behavior.
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Project maintainers have the right and responsibility to remove, edit, or
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reject comments, commits, code, wiki edits, issues, and other contributions
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that are not aligned to this Code of Conduct, or to ban temporarily or
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permanently any contributor for other behaviors that they deem inappropriate,
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threatening, offensive, or harmful.
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## Scope
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This Code of Conduct applies within all project spaces, and it also applies when
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an individual is representing the project or its community in public spaces.
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Examples of representing a project or community include using an official
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project e-mail address, posting via an official social media account, or acting
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as an appointed representative at an online or offline event. Representation of
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a project may be further defined and clarified by project maintainers.
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## Enforcement
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Instances of abusive, harassing, or otherwise unacceptable behavior may be
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reported by contacting the project team at <opensource-conduct@fb.com>. All
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complaints will be reviewed and investigated and will result in a response that
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is deemed necessary and appropriate to the circumstances. The project team is
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obligated to maintain confidentiality with regard to the reporter of an incident.
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Further details of specific enforcement policies may be posted separately.
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Project maintainers who do not follow or enforce the Code of Conduct in good
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faith may face temporary or permanent repercussions as determined by other
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members of the project's leadership.
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## Attribution
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This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4,
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available at https://www.contributor-covenant.org/version/1/4/code-of-conduct.html
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[homepage]: https://www.contributor-covenant.org
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For answers to common questions about this code of conduct, see
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https://www.contributor-covenant.org/faq

‎CONTRIBUTING.md

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# Contributing to hub
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We want to make contributing to this project as easy and transparent as
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possible.
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## Pull Requests
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We actively welcome your pull requests.
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1. Fork the repo and create your branch from `master`.
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2. If you've added code that should be tested, add tests.
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3. If you've changed APIs, update the documentation.
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4. Ensure the test suite passes.
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5. Make sure your code lints.
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6. If you haven't already, complete the Contributor License Agreement ("CLA").
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## Contributor License Agreement ("CLA")
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In order to accept your pull request, we need you to submit a CLA. You only need
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to do this once to work on any of Facebook's open source projects.
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Complete your CLA here: <https://code.facebook.com/cla>
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## Issues
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We use GitHub issues to track public bugs. Please ensure your description is
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clear and has sufficient instructions to be able to reproduce the issue.
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Facebook has a [bounty program](https://www.facebook.com/whitehat/) for the safe
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disclosure of security bugs. In those cases, please go through the process
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outlined on that page and do not file a public issue.
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## License
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By contributing to hub, you agree that your contributions will be licensed
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under the LICENSE file in the root directory of this source tree.

‎assets/hub/CODE_OF_CONDUCT.ipynb

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{
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"cells": [],
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"metadata": {},
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"nbformat": 4,
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"nbformat_minor": 2
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}

‎assets/hub/CONTRIBUTING.ipynb

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{
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"cells": [],
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"metadata": {},
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"nbformat": 4,
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"nbformat_minor": 2
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}

‎assets/hub/pytorch_vision_alexnet.ipynb

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"outputs": [],
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"source": [
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"import torch\n",
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"model = torch.hub.load('pytorch/vision:v0.4.2', 'alexnet', pretrained=True)\n",
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"model = torch.hub.load('pytorch/vision:v0.5.0', 'alexnet', pretrained=True)\n",
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"model.eval()"
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]
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},

‎assets/hub/pytorch_vision_deeplabv3_resnet101.ipynb

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"outputs": [],
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"source": [
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"import torch\n",
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"model = torch.hub.load('pytorch/vision:v0.4.2', 'deeplabv3_resnet101', pretrained=True)\n",
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"model = torch.hub.load('pytorch/vision:v0.5.0', 'deeplabv3_resnet101', pretrained=True)\n",
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"model.eval()"
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]
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},

‎assets/hub/pytorch_vision_densenet.ipynb

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"outputs": [],
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"source": [
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"import torch\n",
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"model = torch.hub.load('pytorch/vision:v0.4.2', 'densenet121', pretrained=True)\n",
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"model = torch.hub.load('pytorch/vision:v0.5.0', 'densenet121', pretrained=True)\n",
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"# or any of these variants\n",
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"# model = torch.hub.load('pytorch/vision:v0.4.2', 'densenet169', pretrained=True)\n",
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"# model = torch.hub.load('pytorch/vision:v0.4.2', 'densenet201', pretrained=True)\n",
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"# model = torch.hub.load('pytorch/vision:v0.4.2', 'densenet161', pretrained=True)\n",
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"# model = torch.hub.load('pytorch/vision:v0.5.0', 'densenet169', pretrained=True)\n",
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"# model = torch.hub.load('pytorch/vision:v0.5.0', 'densenet201', pretrained=True)\n",
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"# model = torch.hub.load('pytorch/vision:v0.5.0', 'densenet161', pretrained=True)\n",
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"model.eval()"
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]
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},

‎assets/hub/pytorch_vision_fcn_resnet101.ipynb

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"outputs": [],
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"source": [
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"import torch\n",
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"model = torch.hub.load('pytorch/vision:v0.4.2', 'fcn_resnet101', pretrained=True)\n",
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"model = torch.hub.load('pytorch/vision:v0.5.0', 'fcn_resnet101', pretrained=True)\n",
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"model.eval()"
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‎assets/hub/pytorch_vision_googlenet.ipynb

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"source": [
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"import torch\n",
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"model = torch.hub.load('pytorch/vision:v0.4.2', 'googlenet', pretrained=True)\n",
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"model = torch.hub.load('pytorch/vision:v0.5.0', 'googlenet', pretrained=True)\n",
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‎assets/hub/pytorch_vision_inception_v3.ipynb

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"import torch\n",
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"model = torch.hub.load('pytorch/vision:v0.5.0', 'inception_v3', pretrained=True)\n",
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‎assets/hub/pytorch_vision_mobilenet_v2.ipynb

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"import torch\n",
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"model = torch.hub.load('pytorch/vision:v0.5.0', 'mobilenet_v2', pretrained=True)\n",
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‎assets/hub/pytorch_vision_resnet.ipynb

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"import torch\n",
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"model = torch.hub.load('pytorch/vision:v0.4.2', 'resnet18', pretrained=True)\n",
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"model = torch.hub.load('pytorch/vision:v0.5.0', 'resnet18', pretrained=True)\n",
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"# or any of these variants\n",
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"# model = torch.hub.load('pytorch/vision:v0.4.2', 'resnet34', pretrained=True)\n",
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"# model = torch.hub.load('pytorch/vision:v0.4.2', 'resnet50', pretrained=True)\n",
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"# model = torch.hub.load('pytorch/vision:v0.4.2', 'resnet101', pretrained=True)\n",
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"# model = torch.hub.load('pytorch/vision:v0.4.2', 'resnet152', pretrained=True)\n",
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"# model = torch.hub.load('pytorch/vision:v0.5.0', 'resnet34', pretrained=True)\n",
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"# model = torch.hub.load('pytorch/vision:v0.5.0', 'resnet50', pretrained=True)\n",
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"# model = torch.hub.load('pytorch/vision:v0.5.0', 'resnet101', pretrained=True)\n",
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"# model = torch.hub.load('pytorch/vision:v0.5.0', 'resnet152', pretrained=True)\n",
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‎assets/hub/pytorch_vision_resnext.ipynb

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"import torch\n",
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"model = torch.hub.load('pytorch/vision:v0.5.0', 'resnext50_32x4d', pretrained=True)\n",
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"# or\n",
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"# model = torch.hub.load('pytorch/vision:v0.4.2', 'resnext101_32x8d', pretrained=True)\n",
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"# model = torch.hub.load('pytorch/vision:v0.5.0', 'resnext101_32x8d', pretrained=True)\n",
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‎assets/hub/pytorch_vision_shufflenet_v2.ipynb

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"import torch\n",
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"model = torch.hub.load('pytorch/vision:v0.5.0', 'shufflenet_v2_x1_0', pretrained=True)\n",
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‎assets/hub/pytorch_vision_squeezenet.ipynb

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"import torch\n",
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"model = torch.hub.load('pytorch/vision:v0.5.0', 'squeezenet1_0', pretrained=True)\n",
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"# or\n",
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"# model = torch.hub.load('pytorch/vision:v0.4.2', 'squeezenet1_1', pretrained=True)\n",
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"# model = torch.hub.load('pytorch/vision:v0.5.0', 'squeezenet1_1', pretrained=True)\n",
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‎assets/hub/pytorch_vision_vgg.ipynb

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"import torch\n",
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"model = torch.hub.load('pytorch/vision:v0.5.0', 'vgg11', pretrained=True)\n",
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"# model = torch.hub.load('pytorch/vision:v0.4.2', 'vgg13_bn', pretrained=True)\n",
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"# model = torch.hub.load('pytorch/vision:v0.4.2', 'vgg16_bn', pretrained=True)\n",
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"# model = torch.hub.load('pytorch/vision:v0.4.2', 'vgg19', pretrained=True)\n",
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"# model = torch.hub.load('pytorch/vision:v0.4.2', 'vgg19_bn', pretrained=True)\n",
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"# model = torch.hub.load('pytorch/vision:v0.5.0', 'vgg11_bn', pretrained=True)\n",
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"# model = torch.hub.load('pytorch/vision:v0.5.0', 'vgg13', pretrained=True)\n",
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"# model = torch.hub.load('pytorch/vision:v0.5.0', 'vgg13_bn', pretrained=True)\n",
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"# model = torch.hub.load('pytorch/vision:v0.5.0', 'vgg16', pretrained=True)\n",
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"# model = torch.hub.load('pytorch/vision:v0.5.0', 'vgg16_bn', pretrained=True)\n",
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"# model = torch.hub.load('pytorch/vision:v0.5.0', 'vgg19', pretrained=True)\n",
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"# model = torch.hub.load('pytorch/vision:v0.5.0', 'vgg19_bn', pretrained=True)\n",
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‎assets/hub/pytorch_vision_wide_resnet.ipynb

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"# load WRN-50-2:\n",
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"model = torch.hub.load('pytorch/vision:v0.5.0', 'wide_resnet50_2', pretrained=True)\n",
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"model = torch.hub.load('pytorch/vision:v0.5.0', 'wide_resnet101_2', pretrained=True)\n",
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