Search Results for "self-host" - Page 6
Sort By:
Showing 178 open source projects for "self-host"
View related business solutions-
$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.
-
Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
-
1
MiniMax-MCP
Official MiniMax Model Context Protocol (MCP) server
...Configuration is handled through JSON files that tell MCP clients how to launch the server (typically via uvx minimax-mcp) and which environment variables to use for the API key, host, and output directory. The README carefully explains region-specific API hosts for global and mainland users to avoid invalid-key errors, and documents both local stdio transport and SSE-based network transport modes. -
2
Lightweight' GAN
Implementation of 'lightweight' GAN, proposed in ICLR 2021
Implementation of 'lightweight' GAN proposed in ICLR 2021, in Pytorch. The main contribution of the paper is a skip-layer excitation in the generator, paired with autoencoding self-supervised learning in the discriminator. Quoting the one-line summary "converge on single gpu with few hours' training, on 1024 resolution sub-hundred images". Augmentation is essential for Lightweight GAN to work effectively in a low data setting. You can test and see how your images will be augmented before they pass into a neural network (if you use augmentation). ... -
3
GeneralAI
Large-scale Self-supervised Pre-training Across Tasks, Languages, etc.
Fundamental research to develop new architectures for foundation models and AI, focusing on modeling generality and capability, as well as training stability and efficiency. -
4
Dataherald
Interact with your SQL database, Natural Language to SQL using LLMs
Dataherald is a platform that allows users to query structured databases using natural language, automatically converting plain English into SQL. It is designed to enable real-time, self-service analytics without needing technical knowledge of databases, making business data easily accessible to non-technical users. Dataherald focuses on speed, accuracy, and scalability for enterprise settings. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
5
KoboldCpp
Run GGUF models easily with a UI or API. One File. Zero Install.
KoboldCpp is an easy-to-use AI text-generation software for GGML and GGUF models, inspired by the original KoboldAI. It's a single self-contained distributable that builds off llama.cpp and adds many additional powerful features. -
6
airda
airda(Air Data Agent
airda(Air Data Agent) is a multi-smart body for data analysis, capable of understanding data development and data analysis needs, understanding data, generating data-oriented queries, data visualization, machine learning and other tasks of SQL and Python codes. -
7
SpiLLI
Decentralized AI Inference
SpiLLI provides infrastructure to manage, host, deploy and run Decentralized AI inference -
8
remotepower
A lightweight control plane for Linux servers
A lightweight control plane for Linux servers. No database, no cloud, no nonsense. One agent per host — everything else lives in flat JSON. v3.2.1 ships SNMP polling for agentless devices, MCP write tools for AI hosts, OIDC SSO, an actionable alerts inbox, and inbound webhooks + syslog. -
9
Conscious Artificial Intelligence
It's possible for machines to become self-aware.
This project is a quest for conscious artificial intelligence. A number of prototypes will be developed as the project progresses. This project has 2 subprojects: Object Pascal based CAI NEURAL API - https://github.com/joaopauloschuler/neural-api Python based K-CAI NEURAL API - https://github.com/joaopauloschuler/k-neural-api A video from the first prototype has been made: http://www.youtube.com/watch?v=qH-IQgYy9zg Above video shows a popperian agent collecting mining ore from 3... -
Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
-
10
Recurrent Interface Network (RIN)
Implementation of Recurrent Interface Network (RIN)
...Additionally, we will try adding an extra linear attention on the main branch as well as self-conditioning in the pixel space. The insight of being able to self-condition on any hidden state of the network as well as the newly proposed sigmoid noise schedule are the two main findings. -
11
VectorDB
A Python vector database you just need, no more, no less
vectordb is a Pythonic vector database offers a comprehensive suite of CRUD (Create, Read, Update, Delete) operations and robust scalability options, including sharding and replication. It's readily deployable in a variety of environments, from local to on-premise and cloud. vectordb delivers exactly what you need - no more, no less. It's a testament to effective Pythonic design without over-engineering, making it a lean yet powerful solution for all your needs. vectordb capitalizes on the... -
12
Nextpy
Self-Modifying Framework from the Future
NextPy is a Python-based framework for building AI-powered automation agents, allowing developers to create intelligent, rule-based workflows. -
13
solo-learn
Library of self-supervised methods for visual representation
A library of self-supervised methods for visual representation learning powered by Pytorch Lightning. A library of self-supervised methods for unsupervised visual representation learning powered by PyTorch Lightning. We aim at providing SOTA self-supervised methods in a comparable environment while, at the same time, implementing training tricks. The library is self-contained, but it is possible to use the models outside of solo-learn. -
14
PromptTools
Open-source tools for prompt testing and experimentation
Welcome to prompttools created by Hegel AI! This repo offers a set of open-source, self-hostable tools for experimenting with, testing, and evaluating LLMs, vector databases, and prompts. The core idea is to enable developers to evaluate using familiar interfaces like code, notebooks, and a local playground. -
15
Sonnet
TensorFlow-based neural network library
Sonnet is a neural network library built on top of TensorFlow designed to provide simple, composable abstractions for machine learning research. Sonnet can be used to build neural networks for various purposes, including different types of learning. Sonnet’s programming model revolves around a single concept: modules. These modules can hold references to parameters, other modules and methods that apply some function on the user input. There are a number of predefined modules that already... -
16
Punica
Serving multiple LoRA finetuned LLM as one
...The system includes specialized CUDA kernels that enable batched GPU operations across different LoRA models simultaneously. This design allows a single GPU cluster to host many task-specific models while maintaining high throughput and minimal latency. The architecture also includes scheduling mechanisms that coordinate requests from multiple tenants and distribute workloads efficiently across available resources. -
17
XAgent
An Autonomous LLM Agent for Complex Task Solving
XAgent is an AI-driven autonomous agent framework capable of handling multi-step tasks across different domains. It enables AI agents to perform decision-making, task planning, and self-learning based on user-defined objectives, making it ideal for automation and research applications. -
18
Sweep AI
Sweep: AI-powered Junior Developer for small features and bug fixes
Let Sweep handle your tech debt so you can focus on the exciting problems. Sweep is an AI junior developer that transforms bug reports & feature requests into code changes. Describe bugs, small features, and refactors like you would to a junior developer and Sweep. -
19
D2L.ai
Interactive deep learning book with multi-framework code
...This open-source book represents our attempt to make deep learning approachable, teaching you the concepts, the context, and the code. The entire book is drafted in Jupyter notebooks, seamlessly integrating exposition figures, math, and interactive examples with self-contained code. Offers sufficient technical depth to provide a starting point on the path to actually becoming an applied machine learning scientist. -
20
Petals
Run 100B+ language models at home, BitTorrent-style
...Beyond classic language model APIs — you can employ any fine-tuning and sampling methods, execute custom paths through the model, or see its hidden states. You get the comforts of an API with the flexibility of PyTorch. You can also host BLOOMZ, a version of BLOOM fine-tuned to follow human instructions in the zero-shot regime — just replace bloom-petals with bloomz-petals. Petals runs large language models like BLOOM-176B collaboratively — you load a small part of the model, then team up with people serving the other parts to run inference or fine-tuning. -
21
AI-Agent-Host
The AI Agent Host is a module-based development environment.
The AI Agent Host integrates several advanced technologies and offers a unique combination of features for the development of language model-driven applications. The AI Agent Host is a module-based environment designed to facilitate rapid experimentation and testing. It includes a docker-compose configuration with QuestDB, Grafana, Code-Server and Nginx. -
22
OpenNMT-tf
Neural machine translation and sequence learning using TensorFlow
...Models are described with code to allow training custom architectures and overriding default behavior. For example, the following instance defines a sequence-to-sequence model with 2 concatenated input features, a self-attentional encoder, and an attentional RNN decoder sharing its input and output embeddings. Sequence to sequence models can be trained with guided alignment and alignment information are returned as part of the translation API. -
23
AI-powered enterprise search engine
AI-powered enterprise search engine
...The platform indexes content from connected systems rather than relying on their native search capabilities, resulting in faster and more relevant results across large datasets. Gerev is built with a strong emphasis on privacy and control, as it can be fully self-hosted, ensuring that sensitive company data remains. -
24
Repo of Tree of Thoughts (ToT)
Implementation of "Tree of Thoughts
...To surmount these challenges, we introduce a new framework for language model inference, Tree of Thoughts (ToT), which generalizes over the popular Chain of Thought approach to prompting language models and enables exploration over coherent units of text (thoughts) that serve as intermediate steps toward problem-solving. ToT allows LMs to perform deliberate decision-making by considering multiple different reasoning paths and self-evaluating choices to decide the next course of action, as well as looking ahead or backtracking when necessary to make global choices. -
25
Free-Auto-GPT
Free AutoGPT enables autonomous AI tasks without paid APIs
Free Auto GPT is an open source project that delivers a simplified version of an autonomous AI agent capable of completing tasks independently. It allows users to run an AutoGPT-style system without relying on paid OpenAI APIs, making it more accessible for experimentation and personal use. Free Auto GPT can take a goal, break it into smaller steps, and execute actions in a loop to achieve results with minimal human input. Designed for ease of use, the project focuses on removing cost...
