Search Results for "load"
Sort By:
Showing 14 open source projects for "load"
View related business solutions-
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
-
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
1
Ollama Python
Ollama Python library
ollama-python is an open-source Python SDK that wraps the Ollama CLI, allowing seamless interaction with local large language models (LLMs) managed by Ollama. Developers use it to load models, send prompts, manage sessions, and stream responses directly from Python code. It simplifies integration of Ollama-based models into applications, supporting synchronous and streaming modes. This tool is ideal for those building AI-driven apps with local model deployment. -
2
DocTR
Library for OCR-related tasks powered by Deep Learning
...Seemlessly process documents for Natural Language Understanding tasks: we provide OCR predictors to parse textual information (localize and identify each word) from your documents. Robust 2-stage (detection + recognition) OCR predictors with pretrained parameters. User-friendly, 3 lines of code to load a document and extract text with a predictor. State-of-the-art performances on public document datasets, comparable with GoogleVision/AWS Textract. Easy integration (available templates for browser demo & API deployment). End-to-End OCR is achieved in docTR using a two-stage approach: text detection (localizing words), then text recognition (identify all characters in the word). ... -
3
jlens
Companion code for the global workspace interpretability paper
...It transports residual-stream vectors from selected layers and positions into the final-layer basis using an averaged input-output Jacobian. The transformed vectors are decoded through the model’s own unembedding into ranked vocabulary predictions. The package can fit new lenses, load saved ones, apply them to prompts, and merge results from parallel fitting jobs. Interactive layer-by-position views reveal how token rankings evolve across the network and compare them with the model’s final output. It supports open-weight Hugging Face decoder models, with Qwen used in the included examples. The repository also provides synthetic evaluation data and an end-to-end notebook, but it is not maintained. -
4
GPTImage2Skill
GPT Image 2 prompt gallery, image prompt library, agentic skill
...The project is designed to help agents and users produce stronger visual outputs without starting from a blank prompt every time. Its gallery is organized into category files so an agent can load only the relevant prompt references instead of overwhelming the context window. It also includes installation paths for skill-capable environments such as Claude Code, Codex, OpenClaw, and other agent runtimes. Overall, it is useful as both a learning resource for prompt structure and a practical toolkit for repeatable image generation workflows. -
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
-
5
CoreNet
CoreNet: A library for training deep neural networks
...CoreNet provides abstractions for data, tensor, and pipeline parallelism, allowing models to scale without code duplication or heavy manual configuration. Its distributed runtime manages synchronization, load balancing, and mixed-precision computation to maximize throughput while minimizing communication bottlenecks. CoreNet integrates tightly with Apple’s proprietary ML stack and hardware, serving as the foundation for research in computer vision, language models, and multimodal systems within Apple AI. The framework includes monitoring tools, fault tolerance mechanisms, and efficient checkpointing for massive training runs. -
6
WTForms
A flexible forms validation and rendering library for Python
...There are a number of community-provided libraries that make integrating with frameworks even better. Flask-WTF integrates with the Flask framework. It can automatically load data from the request, uses Flask-Babel to translate based on user-selected locale, provides full-application CSRF, and more. -
7
aws-devops-zero-to-hero
AWS zero to hero repo for devops engineers to learn AWS in 30 Days
...Later in the curriculum, you move into topics like CloudFormation, CodeCommit/CodePipeline/CodeBuild/CodeDeploy, Terraform on AWS, CloudTrail and Config for compliance, Elastic Load Balancing, and cloud migration strategies. A full day is dedicated to “500 AWS interview questions and answers,” which makes this repo double as an interview prep resource as well as a skills builder. -
8
CommandlineConfig
A library for users to write configurations in Python
CommandlineConfig is a lightweight Python library designed to simplify managing configuration parameters for experiments and applications, especially in research workflows that require frequent tweaking of hyperparameters. It lets you define configuration in familiar Python dictionaries or JSON files and then access nested parameters via dot notation in code, improving readability and reducing boilerplate. One of its core strengths is the ability to override configuration values directly... -
9
NLP Architect
A model library for exploring state-of-the-art deep learning
...The library contains NLP/NLU-related models per task, different neural network topologies (which are used in models), procedures for simplifying workflows in the library, pre-defined data processors and dataset loaders and misc utilities. The library is designed to be a tool for model development: data pre-processing, build model, train, validate, infer, save or load a model. -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
-
10
fastNLP
fastNLP: A Modularized and Extensible NLP Framework
fastNLP is a lightweight framework for natural language processing (NLP), the goal is to quickly implement NLP tasks and build complex models. A unified Tabular data container simplifies the data preprocessing process. Built-in Loader and Pipe for multiple datasets, eliminating the need for preprocessing code. Various convenient NLP tools, such as Embedding loading (including ELMo and BERT), intermediate data cache, etc.. Provide a variety of neural network components and recurrence models... -
11
Ansible Examples
A few starter examples of ansible playbooks, to show features
This repository collects practical, real-world examples of using Ansible to automate infrastructure, deployments, and configurations. Each directory demonstrates a specific use case—ranging from setting up web servers, load balancers, and databases to orchestrating multi-tier applications in cloud environments. The examples highlight common Ansible practices such as organizing inventories, writing reusable playbooks, using roles, and handling variables and templates. They’re designed to be adapted directly into your own infrastructure or to serve as reference blueprints when learning how to structure automation projects. ... -
12
Django REST Pandas
Serves up Pandas dataframes via the Django REST Framework
...This keeps the implementation simple, but also has the nice side effect of making it trivial to provide the source data for your visualizations. This capability can often be leveraged by sending users to the same URL that your visualization code uses internally to load the data. While DRP is primarily a data API, it also provides a default collection of interactive visualizations through the @wq/chart library, and a @wq/pandas loader to facilitate custom JavaScript charts that work well with CSV output served by DRP. These can be used to create interactive time series, scatter, and box plot charts. -
13
pivottablejs
Drag’n’drop Pivot Tables and Charts for Jupyter/IPython Notebook
PivotTable.js is a Javascript Pivot Table and Pivot Chart library with drag-drop interactivity, and it can now be used with Jupyter/IPython Notebook via the pivottablejs module. I first built PivotTable.js with a plan to build an in-browser data analysis tool, and got as far as one where you could load up a CSV file in the browser for display. Since then, however, the Jupyter project has gathered steam and now provides a browser-based interface to some of the most powerful data processing libraries in the world, so it makes sense to interface with it. -
14
Neural Libs
Neural network library for developers
This project includes the implementation of a neural network MLP, RBF, SOM and Hopfield networks in several popular programming languages. The project also includes examples of the use of neural networks as function approximation and time series prediction. Includes a special program makes it easy to test neural network based on training data and the optimization of the network.
- Previous
- You're on page 1
- Next