Search Results for "tiny-core-plus" - Page 8
Sort By:
Showing 1507 open source projects for "tiny-core-plus"
View related business solutions-
Secure File Transfer for Windows with Cerberus by RedwoodCerberus supports unlimited users and connections on a single IP, with built-in encryption, 2FA, and a browser-based web client — all deployable in under 15 minutes with a 25-day free trial.
-
Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
-
1
Nano-vLLM
A lightweight vLLM implementation built from scratch
Nano-vLLM is a lightweight implementation of the vLLM inference engine designed to run large language models efficiently while maintaining a minimal and readable codebase. The project recreates the core functionality of vLLM in a simplified architecture written in approximately a thousand lines of Python, making it easier for developers and researchers to understand how modern LLM inference systems work. Despite its compact design, nano-vllm incorporates advanced optimization techniques such as prefix caching, tensor parallelism, and CUDA graph execution to achieve high performance during model inference. ... -
2
SafeClaw
Chat with it via text and voice
...The assistant offers features such as voice control using fully local speech-to-text (Whisper) and text-to-speech (Piper) capabilities, news aggregation with extractive summarization, and smart home or Bluetooth device control. SafeClaw supports multiple channels, including CLI and Telegram, and avoids prompt injection risk because it doesn’t rely on LLMs for core operations. -
3
ClawRouter
Smart LLM router
...Because distributed AI systems often involve many services, agents, and runtime components interacting with each other and with external APIs, ClawRouter helps ensure that communication paths remain clear, efficient, and adaptable as systems scale. The framework supports plugin-based extensions so developers can define custom protocols, transformation hooks, and monitoring handlers without modifying core routing logic. It also offers operational features like health checking, metrics reporting, and failure handling that make production deployments more reliable. -
4
AutoCoder
A long-running autonomous coding agent powered by the Claude Agent
...It is built to support iterative refinement: after generating an initial draft, you can provide feedback or corrections, and the system will adjust the output to match evolving intentions. The core idea is to accelerate software production while preserving correctness and readability, minimizing the cognitive overhead that comes from switching between concept and implementation. Its architecture typically integrates language models with static analysis and template logic so that generated code is not only syntactically valid but also idiomatic and testable. -
AI-powered service management for IT and enterprise teamsGive your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
-
5
Bifrost
The Fastest LLM Gateway with built in OTel observability
...It also includes observability with built-in metrics, tracing, logging, and supports governance features like rate limiting, access control, and cost budgeting. The architecture is modular: there is a core engine, plugin layers, and transport layers (HTTP APIs). -
6
Tiktoken
tiktoken is a fast BPE tokeniser for use with OpenAI's models
...“cl100k_base”) and lets users switch encoding names to match different model contexts. It also offers extension mechanisms so that custom encodings can be registered. Internally, it includes the core tokenizer logic (often implemented in Rust or efficient lower-level code), APIs for encoding, decoding, and counting tokens, and binding layers to Python (and sometimes other languages) for easy use. -
7
DeepCTR-Torch
Easy-to-use,Modular and Extendible package of deep-learning models
DeepCTR-Torch is an easy-to-use, Modular and Extendible package of deep-learning-based CTR models along with lots of core components layers that can be used to build your own custom model easily.It is compatible with PyTorch.You can use any complex model with model.fit() and model.predict(). With the great success of deep learning, DNN-based techniques have been widely used in CTR estimation tasks. The data in the CTR estimation task usually includes high sparse,high cardinality categorical features and some dense numerical features. ... -
8
Haiku
JAX-based neural network library
Haiku is a library built on top of JAX designed to provide simple, composable abstractions for machine learning research. Haiku is a simple neural network library for JAX that enables users to use familiar object-oriented programming models while allowing full access to JAX’s pure function transformations. Haiku is designed to make the common things we do such as managing model parameters and other model state simpler and similar in spirit to the Sonnet library that has been widely used... -
9
DeepCTR
Package of deep-learning based CTR models
DeepCTR is a Easy-to-use,Modular and Extendible package of deep-learning based CTR models along with lots of core components layers which can be used to easily build custom models. You can use any complex model with model.fit(), and model.predict(). Provide tf.keras.Model like interface for quick experiment. Provide tensorflow estimator interface for large scale data and distributed training. It is compatible with both tf 1.x and tf 2.x. With the great success of deep learning,DNN-based techniques have been widely used in CTR prediction task. ... -
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
-
10
ggml
Tensor library for machine learning
ggml is an open-source tensor library designed for efficient machine learning computation with a focus on running models locally and with minimal dependencies. Written primarily in C and C++, the library provides low-level tensor operations and automatic differentiation that allow developers to implement machine learning algorithms and neural networks efficiently. The project emphasizes portability and performance, enabling machine learning inference across a wide range of hardware... -
11
LiteRT
LiteRT, successor to TensorFlow Lite
LiteRT is Google's next-generation on-device machine learning framework and the successor to TensorFlow Lite, designed for high-performance AI and generative AI deployment across edge devices. It provides efficient model conversion, optimization, and runtime execution while leveraging hardware acceleration from CPUs, GPUs, and NPUs. LiteRT supports a wide range of platforms, including Android, iOS, Linux, macOS, Windows, web environments, and IoT devices. The framework simplifies on-device... -
12
deep-q-learning
Minimal Deep Q Learning (DQN & DDQN) implementations in Keras
The deep-q-learning repository authored by keon provides a Python-based implementation of the Deep Q-Learning algorithm — a cornerstone method in reinforcement learning. It implements the core logic needed to train an agent using Q-learning with neural networks (i.e. approximating Q-values via deep nets), setting up environment interaction loops, experience replay, network updates, and policy behavior. For learners and researchers interested in reinforcement learning, this repo offers a concrete, runnable example bridging theory and practice: you can execute the code, play with hyperparameters, observe convergence behavior, and see how deep Q-learning learns policies over time in standard environments. ... -
13
comfyui-mixlab-nodes
Workflow and speech recognition app
...The project also brings Real-time Design features like screen capture and floating video nodes, enabling creative pipelines that mix live screen content, generative models, and visual effects. For audio and speech, it provides nodes for SpeechRecognition and SpeechSynthesis, plus workflows that combine voice generation with real-time face swapping and other audio-visual effects. On the AI side, it integrates multiple LLM providers (cloud and local), supports OpenAI-compatible endpoints, Siliconflow models, and includes prompt-focused utilities for random prompt generation, Chinese prompts, clip interrogation. -
14
Lightly
A python library for self-supervised learning on images
...Our solution can be applied before any data annotation step and the learned representations can be used to visualize and analyze datasets. This allows selecting the best core set of samples for model training through advanced filtering. We provide PyTorch, PyTorch Lightning and PyTorch Lightning distributed examples for each of the models to kickstart your project. Lightly requires Python 3.6+ but we recommend using Python 3.7+. We recommend installing Lightly in a Linux or OSX environment. With lightly, you can use the latest self-supervised learning methods in a modular way using the full power of PyTorch. ... -
15
Kaldi
kaldi-asr/kaldi is the official location of the Kaldi project
Kaldi is an open source toolkit for speech recognition research. It provides a powerful framework for building state-of-the-art automatic speech recognition (ASR) systems, with support for deep neural networks, Gaussian mixture models, hidden Markov models, and other advanced techniques. The toolkit is widely used in both academia and industry due to its flexibility, extensibility, and strong community support. Kaldi is designed for researchers who need a highly customizable environment to... -
16
mlx
MLX: An array framework for Apple silicon
MlX offers a local web interface to browse, download, and run ML models via Hugging Face or local sources. It supports searching by tags or tasks, visualization of model metadata, quick inference demos, automatic setup of runtime environments, and works with PyTorch, TensorFlow, and ONNX. Ideal for researchers exploring and testing models via browser. -
17
improve
Use your most capable model to audit your codebase
improve is an agent skill that audits a codebase and writes implementation plans for other agents or humans to execute. Its core idea is to use a stronger model for understanding, judgment, and planning, then hand the actual implementation to cheaper or separate execution agents. The skill does not modify code by default, because its main output is a self-contained plan. It can run full, quick, deep, security-focused, branch-scoped, and feature-suggestion audits. -
18
holaOS
An Open Agent Computer for ANY digital work
holaOSc is an AI-native operating system concept designed to integrate intelligent agents directly into the core of the computing environment. It provides a framework where AI agents manage tasks, workflows, and interactions across applications. The system emphasizes seamless automation, allowing users to interact with their computer through natural language and high-level instructions. It integrates memory, context awareness, and task orchestration into a unified environment. ... -
19
PromptBin
A free guide for learning to create ChatGPT3 Prompts
PromptBin is an open-source prompt engineering resource and lightweight web application designed to help users discover, organize, and reuse effective prompts for large language models like ChatGPT. At its core, the project acts as a curated and structured library of prompts across a wide variety of use cases, including writing, brainstorming, debugging, and coding, making it particularly useful for both beginners and advanced users. The repository is also intended as a foundation for building custom prompt management systems, allowing developers or teams to fork and adapt it into internal tools or client-facing solutions. ... -
20
ShoppingAgent
Custom Chinese chatbot with Seq2Seq, GPT, and agent features
...ShoppingAgent is structured to support experimentation across different deep learning frameworks such as TensorFlow, PyTorch, and MindSpore, giving developers flexibility in how they train and deploy models. In addition to core chatbot functionality, the project introduces agent-based capabilities, enabling practical use cases like automated workflows and task-oriented assistants. It also includes support for small language models and local training scripts, making it accessible for users with limited computational resources. ShoppingAgent can be applied to scenarios such as customer service, question answering, and casual conversation. -
21
Ant Design X
Experimental Ant Design extensions for advanced UI patterns
Ant Design X is an experimental extension project built around the Ant Design ecosystem, focusing on exploring advanced user interface patterns and next-generation component designs. It serves as a space for prototyping and validating ideas that go beyond the core Ant Design library, allowing developers to experiment with more complex interactions and layouts. Ant Design X emphasizes flexibility and extensibility, enabling developers to adapt components to modern application needs. It often includes higher-level abstractions and enhanced UI capabilities that are not yet part of the stable design system. ... -
22
course.fast.ai
The fast.ai course notebooks
course22 is the official repository containing the notebooks, slides, and supporting materials for the 2022 edition of the fast.ai course Practical Deep Learning for Coders. The repository serves as the core educational resource for the course, providing learners with hands-on exercises and coding tutorials that accompany each lecture. The project emphasizes learning deep learning through experimentation rather than purely theoretical study, encouraging students to build models and analyze results directly in Jupyter notebooks. The repository includes lesson notebooks, slide presentations, spreadsheets, and supplementary materials that help students understand neural networks, computer vision, and natural language processing tasks. ... -
23
Deep Learning Interviews book
Hundreds of fully solved job interview questions
...Each question is accompanied by detailed solutions that explain the reasoning behind the answers and the theoretical concepts involved. In addition to interview preparation, the material also serves as a condensed overview of many core topics taught in graduate-level machine learning programs. -
24
The Algorithms - C++ #
Collection of various algorithms in mathematics, machine learning
TheAlgorithms/C-Plus-Plus is a large open-source repository that collects implementations of many classic algorithms and data structures written in the C++ programming language. The project is part of the broader “The Algorithms” initiative, which maintains algorithm implementations in several programming languages to support education and knowledge sharing. -
25
Free ChatGPT Site List
It collects and organizes a wide variety of ChatGPT resources
...The project emphasizes simplicity and quick access rather than complex automation, and it has attracted significant community attention before being archived by its maintainer. Because it aggregates external resources rather than implementing core AI functionality, its value lies in discovery and convenience. The repository is now read-only, preserving it as a snapshot of the AI tooling landscape at the time of archiving. Overall, Carrot serves as a community-curated directory of AI access points and related tools.
