Search Results for "source code claude code" - Page 57
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Showing 2475 open source projects for "source code claude code"
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MMdnn
Tools to help users inter-operate among deep learning frameworks
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML. MMdnn is a comprehensive and cross-framework tool to convert, visualize and diagnose deep learning (DL) models. The "MM" stands for model management, and "dnn" is the acronym of deep neural network. We implement a universal converter to convert DL models between frameworks,... -
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pytorch-tutorial
PyTorch Tutorial for Deep Learning Researchers
pytorch-tutorial is a highly popular educational repository that teaches deep learning with PyTorch through step-by-step examples and well-structured lessons. It is designed primarily for beginners and intermediate practitioners who want to understand PyTorch fundamentals and quickly move toward building real neural network models. The repository walks users through core concepts such as tensors, autograd, neural network modules, convolutional networks, recurrent networks, and transfer... -
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Free Queue Manager
Web based python-flask Queue management system
A web based management system developed for the purpose of easing the process of orgnizing queues and lines. Like many other (QMS)s Queue Management Systems, FQM does provide a basic dashboard to allow the users of the system and customers alike to interact with the system via a basic yet simple user interface . Brief user guide can be found on https://fqms.github.io/images/user_guide.pdf -
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Brand new cheatsheets and handouts
Matplotlib 3.1 cheat sheet
The Brand new cheatsheets and handouts repo is a compact, quick-reference summary of the most commonly used plotting commands and configurations in Matplotlib, intended to serve as a handy reference for experienced users who want to recall syntax or find the right function without digging into full documentation. It lays out common use cases (plot types, styling, figure configuration, saving/exporting, subplot layout, etc.) in a concise and organized format — often serving as a “cheat sheet”... -
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StellarGraph
Machine Learning on Graphs
StellarGraph is a Python library for machine learning on graphs and networks. The StellarGraph library offers state-of-the-art algorithms for graph machine learning, making it easy to discover patterns and answer questions about graph-structured data. It can solve many machine learning tasks. Graph-structured data represent entities as nodes (or vertices) and relationships between them as edges (or links), and can include data associated with either as attributes. For example, a graph can... -
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Tensorflow and deep learning
A crash course in six episodes for software developers
Tensorflow and deep learning repository is an educational deep learning crash course designed to help software developers quickly understand and apply machine learning concepts without requiring advanced academic background. It is structured as a series of guided lessons that combine theoretical explanations, practical examples, and runnable code, allowing learners to build intuition while actively experimenting with models. The repository covers core neural network concepts such as weights,... -
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DETR
End-to-end object detection with transformers
PyTorch training code and pretrained models for DETR (DEtection TRansformer). We replace the full complex hand-crafted object detection pipeline with a Transformer, and match Faster R-CNN with a ResNet-50, obtaining 42 AP on COCO using half the computation power (FLOPs) and the same number of parameters. Inference in 50 lines of PyTorch. What it is. Unlike traditional computer vision techniques, DETR approaches object detection as a direct set prediction problem. It consists of a set-based... -
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SageMaker Containers
Create SageMaker-compatible Docker containers
Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime and reliable training process. The SageMaker Training Toolkit can be easily added to... -
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ENAS in PyTorch
PyTorch implementation of "Efficient Neural Architecture Search
ENAS in PyTorch is a PyTorch implementation of Efficient Neural Architecture Search (ENAS), a method that automates the design of neural network architectures through reinforcement learning and parameter sharing. The repository demonstrates how a controller network can explore a large search space and discover high-performing architectures while dramatically reducing the computational cost traditionally associated with neural architecture search. It is primarily intended as a research and... -
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...Installation Videos! Part 1: http://youtu.be/rnv2VLcG-eI Part 2: http://youtu.be/eFudbMWHNlQ Special thanks to Wells Oliver for the code for downloading Retrosheet files. And the Chadwick project for its Retrosheet tools. https://sourceforge.net/projects/chadwick/?source=recommended
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Python Handout
Turn Python scripts into handouts with Markdown and figures
Handout is a lightweight library for embedding rich, interactive components such as exercises, charts, and interactive diagrams directly into static documents like Markdown, Jupyter notebooks, or static HTML pages, enabling authors to create more engaging technical handouts, tutorials, and interactive essays. It’s particularly aimed at educators, presenters, and researchers who want to make their written material come alive with runnable demonstrations and interactive problem sets without... -
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Tensor2Tensor
Library of deep learning models and datasets
Deep Learning (DL) has enabled the rapid advancement of many useful technologies, such as machine translation, speech recognition and object detection. In the research community, one can find code open-sourced by the authors to help in replicating their results and further advancing deep learning. However, most of these DL systems use unique setups that require significant engineering effort and may only work for a specific problem or architecture, making it hard to run new experiments and... -
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Reliable Metrics for Generative Models
Code base for the precision, recall, density, and coverage metrics
Reliable Fidelity and Diversity Metrics for Generative Models (ICML 2020). Devising indicative evaluation metrics for the image generation task remains an open problem. The most widely used metric for measuring the similarity between real and generated images has been the Fréchet Inception Distance (FID) score. Because it does not differentiate the fidelity and diversity aspects of the generated images, recent papers have introduced variants of precision and recall metrics to diagnose those... -
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MGFVisor
Visor for mass spectrometry MGF files
Visor for mass spectrometry MGF files (Python 3 version). For more information, you can have a look at the README.md file in the source code tree: https://sourceforge.net/p/lp-csic-uab/mgfvisor3/code/ci/default/tree/README.md -
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Kopf
A Python framework to write Kubernetes operators
Kopf —Kubernetes Operator Pythonic Framework, is a framework and a library to make Kubernetes operator's development easier, just in a few lines of Python code. The main goal is to bring the Domain-Driven Design to the infrastructure level, with Kubernetes being an orchestrator/database of the domain objects (custom resources), and the operators containing the domain logic (with no or minimal infrastructure logic). -
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Retro
Retro Games in Gym
RETRO (Retrieval-Enhanced Transformer) is a large language model architecture developed by OpenAI that augments transformer models with a retrieval mechanism. Instead of relying solely on learned parameters, RETRO retrieves relevant documents from a large external database during inference, allowing it to ground responses in external knowledge. This design improves factual accuracy, reduces hallucinations, and enables smaller models to perform comparably to much larger ones by leveraging... -
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EasierMGF
Converts RAW Thermo Files into MGF files
Converts RAW Thermo Files into MGF files (Python 3 version). For more information, you can have a look at the README.md file in the source code tree: https://sourceforge.net/p/lp-csic-uab/easiermgf3/code/ci/default/tree/README.md - Gallardo, Ó., Ovelleiro, D., Gay, M., Carrascal, M., & Abian, J. (2014). A collection of open source applications for mass spectrometry data mining. PROTEOMICS, 14(20), 2275–2279. https://doi.org/10.1002/pmic.201400124 -
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Python4Proteomics Course
Python course for Proteomics analysis
Python course (in Spanish) for Proteomics analysis using basically Jupyter NoteBooks. For more information, you can have a look at the readme.md file in the source code tree: https://sourceforge.net/p/lp-csic-uab/p4p/code/ci/default/tree/readme.md -
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KimPeptid
Analyzes Peptides Properties (Python 3 version)
Analyzes Peptides Properties (Python 3 version). For more information, you can have a look at the README.md file in the source code tree: https://sourceforge.net/p/lp-csic-uab/kimpeptid3/code/ci/default/tree/README.md -
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DeepFaceLab
The leading software for creating deepfakes
DeepFaceLab is currently the world's leading software for creating deepfakes, with over 95% of deepfake videos created with DeepFaceLab. DeepFaceLab is an open-source deepfake system that enables users to swap the faces on images and on video. It offers an imperative and easy-to-use pipeline that even those without a comprehensive understanding of the deep learning framework or model implementation can use; and yet also provides a flexible and loose coupling structure for those who want to strengthen their own pipeline with other features without having to write complicated boilerplate code. -
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MADDPG
Code for the MADDPG algorithm from a paper
MADDPG (Multi-Agent Deep Deterministic Policy Gradient) is the official code release from OpenAI’s paper Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments. The repository implements a multi-agent reinforcement learning algorithm that extends DDPG to scenarios where multiple agents interact in shared environments. Each agent has its own policy, but training uses centralized critics conditioned on the observations and actions of all agents, enabling learning in... -
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End-to-End Negotiator
Deal or No Deal? End-to-End Learning for Negotiation Dialogues
End-to-End Negotiator is a PyTorch-based research framework developed by Facebook AI Research to train neural agents capable of conducting strategic negotiations in natural language. The project implements the models presented in two key papers: “Deal or No Deal? End-to-End Learning for Negotiation Dialogues” and “Hierarchical Text Generation and Planning for Strategic Dialogue”. It enables agents to plan, reason, and communicate effectively to maximize outcomes in multi-turn negotiations... -
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javalang
Pure Python Java parser and tools
javalang is a pure Python library for working with Java source code. javalang provides a lexer and parser targeting Java 8. The implementation is based on the Java language spec. -
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API Correios
API correios.com.br in Python
pycorreios is a Python library aimed at interacting with Brazil’s postal service (Correios) APIs, making it easier for developers to track shipments, calculate postage, query service availability, and integrate with Brazilian e-commerce flows. The library abstracts the raw SOAP or REST endpoints exposed by Correios, providing Pythonic methods to perform common tasks like tracking a package by its code or computing shipping cost/lead time between postal codes. It handles serialization and mapping of API responses into Python objects so developers don’t manually parse raw XML or JSON. With this tool, developers building Brazilian market e-commerce or logistics solutions can integrate postal services smoothly. Because it is open source, improvements can be contributed to support new endpoints, changes in the postal service API, or additional features like caching or async requests. -
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TCellXTalk
TCellXTalk Web-App from LP CSIC/UAB
TCellXTalk is a comprehensive database of experimentally detected phosphorylation, ubiquitination and acetylation sites in human T cells. The web-app at www.TCellXTalk.org makes TCellXTalk accessible from Internet, and enables the in silico prediction of potential co-modified peptides to facilitate their experimental detection, using targeted or directed mass spectrometry, for the study of protein post-translational modification cross-talk. More detailed information on TCellXTalk and...
