Deep Learning, NLP, NMT, AI, ML
A very simple tool that compresses the overall size of the ONNX model by aggregating duplicate constant values as much as possible. Simple Constant value Shrink for ONNX. If the same constant tensor is found by scanning the entire graph for Constant values, it is aggregated into a single constant tensor. Ignore scalar values. Ignore variables. 1. Setup
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Installation Go into the Steam Deck Settings Under System -> System Settings toggle Enable Developer Mode Scroll the sidebar all the way down and click on Developer Under Miscellaneous, enable CEF Remote Debugging Place the executable under ~/homebrew/services/plugin_loader. Do not change the name of the file. Place the plugin_manager.service file under /etc/systemd/system Open a Terminal and type systemctl –now –user enable plugin_manager Install Plugins Simply copy the plugin’s .py file into ~/homebrew/plugins Features Clean injecting and loading of one or […]
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Setting up the requirements Download the Python installer from here Make sure “Add Python 3.9 to PATH is ticked Click on Customize installation, and make sure everything is ticked Click on “Next” Make sure “Add Python to environment variables” is ticked” Click install. and let it go Python Package Requirements To run the bot for the first time, install the requirements. Windows pip install -r requirements.txt simply open the directory you’ve extracted the bot to, and type cmd in the […]
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Kehong Gong*, Bingbing Li*, Jianfeng Zhang*, Tao Wang*, Jing Huang, Bi Mi, Jiashi Feng, Xinchao Wang CVPR 2022 (Oral Presentation, arxiv) Framework Pose-triplet contains three components: estimator, imitator and hallucinator The three components form dual-loop during the training process, complementing and strengthening one another. Improvement through co-evolving Here is imitated motion of different rounds, the estimator and imitator get improved over the rounds of training, and thus the imitated motion becomes more accurate and realistic from round 1 to 3. […]
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This repo contains the implementation of our paper: DeepDPM: Deep Clustering With An Unknown Number of Clusters Meitar Ronen, Shahaf Finder and Oren Freifeld. DeepDPM clustering example on 2D data. On the left: DeepDPM’s predicted clusters’ assignments, centers and covariances. On the right: Clusters colored by the GT labels, and the net’s decision boundary. Examples of the clusters found by DeepDPM on the ImageNet Dataset: Table of Contents Introduction Installation Training Citation
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Build custom Vega/Vega-Lite dashboards in Datasette, for presentation-ready plots and visualizations. Installation Install this plugin in the same environment as Datasette. $ datasette install datasette-vega-dashboards Tutorial See the example fixture in example_fixture for a minimal example. You can run the fixture via: datasette -m metadata.json –template-dir templates/ sleep_log.db and then open http://127.0.0.1:8001/sleep_log/read_sleep to see the dashboard. In the minimal example, we create a canned query in metadata.json:
Read moreOpenSphere is a hyperspherical face recognition library based on PyTorch. See the project homepage. Introduction OpenSphere provides a consistent and unified training and evaluation framework for hyperspherical face recognition research. The framework decouples the loss function from the other varying components such as network architecture, optimizer, and data augmentation. It can fairly compare different loss functions in hyperspherical face recognition on popular benchmarks, serving as a transparaent platform to reproduce published results. Supported Projects SphereFace: Deep Hypersphere Embedding for […]
Read moreThis project is live at place.thatguyalex.com. Running scraper locally Install Python and all dependencies from scraper.py imports (if you want to create a requirements.txt, please make a PR and i’ll merge it) Edit authparams.py with your reddit username and password, and then add an oauth app of type script Field AUTH_TOKEN can be left empty, it is used for manual overrides Run scraper.py Running website locally Pull requests and suggestions welcome GitHub View Github
Read moreCreating APIs, or application programming interfaces, is an important part of making your software accessible to a broad range of users. In this video course, you’ll learn the main concepts of FastAPI and how to use it to quickly create web APIs that implement best practices by default. By the end of it, you’ll be able to start creating production-ready web APIs, and you’ll have the understanding needed to go deeper and learn more for your specific use cases. In […]
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Data Utilities and Processing Generalized for All CDP Instances Installation Stable Release: pip install cdp-data Development Head: pip install git+https://github.com/CouncilDataProject/cdp-data.git Documentation For full package documentation please visit councildataproject.github.io/cdp-data. Quickstart Development See CONTRIBUTING.md for information related to developing the code. MIT license GitHub View Github
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