Search Results for "vs code window8"
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Showing 19 open source projects for "vs code window8"
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Grafana: The open and composable observability platformGrafana is the open source analytics & monitoring solution for every database.
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Keep company data safe with Chrome EnterpriseMake AI work your way with Chrome Enterprise. Block unapproved sites and set custom data controls that align with your company's policies.
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CodeGeeX
CodeGeeX: An Open Multilingual Code Generation Model (KDD 2023)
...CodeGeeX also powers IDE plugins for VS Code and JetBrains, offering features like code completion, translation, debugging, and annotation. The model supports Ascend 910 and NVIDIA GPUs, with optimizations like quantization and FasterTransformer acceleration for faster inference. -
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Pyright
Static type checker for Python
...Each environment can specify different module search paths, python language versions, and platform targets. Type inference for function return values, instance variables, class variables, and globals. Type guards that understand conditional code flow constructs like if/else statements. Type hinting generics in standard collections. Pyright ships as both a command-line tool and a VS Code extension that provides many powerful features that help improve programming efficiency. The VS Code extension supports many time-saving language features. -
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CodeGeeX2
CodeGeeX2: A More Powerful Multilingual Code Generation Model
...With improved inference efficiency, quantization options, and multi-query/flash attention, CodeGeeX2 achieves faster generation speeds and lightweight deployment, requiring as little as 6GB GPU memory at INT4 precision. Its backend powers the CodeGeeX IDE plugins for VS Code, JetBrains, and other editors, offering developers interactive AI assistance with features like infilling and cross-file completion. -
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DeepSeek Coder
DeepSeek Coder: Let the Code Write Itself
DeepSeek-Coder is a series of code-specialized language models designed to generate, complete, and infill code (and mixed code + natural language) with high fluency in both English and Chinese. The models are trained from scratch on a massive corpus (~2 trillion tokens), of which about 87% is code and 13% is natural language. This dataset covers project-level code structure (not just line-by-line snippets), using a large context window (e.g. 16K) and a secondary fill-in-the-blank objective to encourage better contextual completions and infilling. ... -
Cloud-based help desk software with ServoDeskWhat if You Could Automate 90% of Your Repetitive Tasks in Under 30 Days? At ServoDesk, we help businesses like yours automate operations with AI, allowing you to cut service times in half and increase productivity by 25% - without hiring more staff.
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LLM Foundry
LLM training code for MosaicML foundation models
Introducing MPT-7B, the first entry in our MosaicML Foundation Series. MPT-7B is a transformer trained from scratch on 1T tokens of text and code. It is open source, available for commercial use, and matches the quality of LLaMA-7B. MPT-7B was trained on the MosaicML platform in 9.5 days with zero human intervention at a cost of ~$200k. Large language models (LLMs) are changing the world, but for those outside well-resourced industry labs, it can be extremely difficult to train and deploy... -
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Sweetviz
Visualize and compare datasets, target values and associations
Sweetviz is an open-source Python library that generates beautiful, high-density visualizations to kickstart EDA (Exploratory Data Analysis) with just two lines of code. Output is a fully self-contained HTML application. The system is built around quickly visualizing target values and comparing datasets. Its goal is to help quick analysis of target characteristics, training vs testing data, and other such data characterization tasks. Shows how a target value (e.g. "Survived" in the Titanic dataset) relates to other features. ... -
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MobileCLIP
Implementation of "MobileCLIP" CVPR 2024
MobileCLIP is a family of efficient image-text embedding models designed for real-time, on-device retrieval and zero-shot classification. The repo provides training, inference, and evaluation code for MobileCLIP models trained on DataCompDR, and for newer MobileCLIP2 models trained on DFNDR. It includes an iOS demo app and Core ML artifacts to showcase practical, offline photo search and classification on iPhone-class hardware. Project notes highlight latency/accuracy trade-offs, with... -
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Taipy
Turns Data and AI algorithms into production-ready web applications
...Struggle with sluggish performance and excessive memory usage, as every data point demands processing. Large datasets become cumbersome, complicating the user experience and data analysis. Scenarios are made easy with Taipy Studio. A powerful VS Code extension that unlocks a convenient graphical editor. Get your methods invoked at a certain time or intervals. Enjoy a variety of predefined themes or build your own. -
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EasyR1
An Efficient, Scalable, Multi-Modality RL Training Framework
...It emphasizes memory-efficient training strategies so you can train long-context or reasoning-dense models on commodity GPUs. The framework is also organized to help you compare training strategies (e.g., pure SFT vs. preference optimization) so you can see what actually moves metrics in math, code, and multi-step reasoning. For teams exploring open reasoning models, EasyR1 provides an opinionated yet flexible path from dataset to deployable checkpoints. -
Valant Behavioral Health EHRUnlike other non-specialized EMR software, Valant is built exclusively for behavioral health. It is designed to increase the administrative and clinical efficiency of your practice and includes built-in outcome measures, billing, reporting, telehealth, and clinical documentation tools – all tailored to the unique needs of mental health.
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Automated Interpretability
Code for Language models can explain neurons in language models paper
The automated-interpretability repository implements tools and pipelines for automatically generating, simulating, and scoring explanations of neuron (or latent feature) behavior in neural networks. Instead of relying purely on manual, ad hoc interpretability probing, this repo aims to scale interpretability by using algorithmic methods that produce candidate explanations and assess their quality. It includes a “neuron explainer” component that, given a target neuron or latent feature,... -
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DBRplot
Plots reflectivity response of Distributed Braggs Reflector mirrors
A free windows software for designing and modelling of dielectric anti-reflection coating and Fabry-Perot cavity effects based on Distributed Braggs Reflector (DBR) mirrors. Read 'readme.txt' file before you use this application. Also, have a look at the "Fabry-Perot cavity" diagram to get a feel of the structure of your cavity. The code is written based on the Transfer Matrix Method for TE incidence. Clever insertion of the input parameters in the GUI will let you simulate the reflectivity... -
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BARS_checkers
BARS - a program for playing checkers
...In this program, you can play with a robot of different difficulty levels, train your memory, solve tasks, memorize openings, save games played. Enjoy using it :) source code: https://github.com/Ni3nayka/BARS-international VK-group: https://vk.com/bars_checkers if you have a problem starting the program, try: 1) update net.framework 2) update VS MS C++ WARNING: the program works only with windows x64 -
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VSCode-LaTeX-Inkscape
A way to integrate LaTeX, VS Code, and Inkscape in macOS
A way to integrate LaTeX, VS Code, and Inkscape in macOS. I use LaTeX heavily for both academic work and professional work, and I think I'm quite proficient in terms of typing things out in LaTeX. But when I see the mind-blowing blog posts from Gilles Castel (RIP)-How I'm able to take notes in mathematics lectures using LaTeX and Vim and also How I draw figures for my mathematical lecture notes using Inkscape, I realize that I'm still far from fast, so I decided to adapt the whole setup from Linux-Vim to macOS-VS Code. -
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Guided Diffusion
Codebase for Diffusion Models Beat GANS on Image Synthesis
...It is derived from OpenAI’s improved-diffusion work, enhanced to include guided generation where a classifier (or other guidance mechanism) can steer sampling toward desired classes or attributes. The code provides model definitions (UNet, diffusion schedules), sampling and training scripts, and utilities for guidance and evaluation. A key insight is that combining diffusion sampling with classifier gradients allows fine control over the generated images, trading off diversity vs fidelity. The repository includes scripts such as image_train.py, image_sample.py, and classifier_train.py to train diffusion models, generate samples, and train guiding classifiers. ... -
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ML workspace
All-in-one web-based IDE specialized for machine learning
...This workspace is the ultimate tool for developers preloaded with a variety of popular data science libraries (e.g., Tensorflow, PyTorch, Keras, Sklearn) and dev tools (e.g., Jupyter, VS Code, Tensorboard) perfectly configured, optimized, and integrated. Usable as remote kernel (Jupyter) or remote machine (VS Code) via SSH. Easy to deploy on Mac, Linux, and Windows via Docker. Jupyter, JupyterLab, and Visual Studio Code web-based IDEs.By default, the workspace container has no resource constraints and can use as much of a given resource as the host’s kernel scheduler allows. -
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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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HDL Checker
Repurposing existing HDL tools to help writing better code
HDL Checker is a language server that wraps VHDL/Verilg/SystemVerilog tools that aims to reduce the boilerplate code needed to set things up. It supports Language Server Protocol or a custom HTTP interface; can infer the library VHDL files likely to belong to, besides working out mixed language dependencies, compilation order, interpreting some compiler messages and providing some (limited) static checks. Notice that currently, the unused reports has caveats, namely declarations with the... -
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Python Patterns
A collection of design patterns/idioms in Python
Python-Patterns is a repository collecting implementations of many classical design patterns and idioms, written in Python. It serves as an educational resource: showing how to implement creational, structural, behavioral, testability, and other patterns in a Pythonic style (or sometimes less so), illustrating trade-offs, different styles, and use cases. It’s intended for learners or developers interested in software architecture or design, rather than as a production library. Includes... -
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makeprojects
Auto generate VS, Codewarrior, Codeblocks, XCode projects
This tool will scan your directory for source files and then generate a project file for Codeblocks, XCode, Visual Studio, Metrowerks CodeWarrior, FreeScale Codewarrior. It runs on Linux, MacOSX and Windows and can generate the files for any host from any platform. Great care is taken to make sure project file updates change as little as possible to make source control change lists as minimal as possible. This is the main IDE project file generator used by Olde Sküül!
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