Search Results for "node-sass" - Page 3
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Showing 142 open source projects for "node-sass"
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AReal
Lightning-Fast RL for LLM Reasoning and Agents. Made Simple & Flexible
AReaL is an open source, fully asynchronous reinforcement learning training system. AReal is designed for large reasoning and agentic models. It works with models that perform reasoning over multiple steps, agents interacting with environments. It is developed by the AReaL Team at Ant Group (inclusionAI) and builds upon the ReaLHF project. Release of training details, datasets, and models for reproducibility. It is intended to facilitate reproducible RL training on reasoning / agentic tasks,... -
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OmAgent
Build multimodal language agents for fast prototype and production
...The framework provides abstractions and infrastructure for building AI agents that operate on text, images, video, and audio while maintaining a relatively simple interface for developers. Instead of forcing developers to implement complex orchestration logic manually, the system manages task scheduling, worker coordination, and node optimization behind the scenes. Its architecture uses a graph-based workflow engine where tasks are represented as nodes in a directed workflow, enabling modular composition of complex reasoning pipelines. The framework also includes support for various reasoning strategies commonly used in language agents, such as chain-of-thought prompting, self-consistency reasoning, and ReAct-style decision loops. -
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EKS Best Practices
A best practices guide for day 2 operations
...The repository is maintained by AWS but open to contributions from the community, making it a living document that evolves as Kubernetes and AWS features evolve. Each section dives into operational details—for example, how to manage IAM roles for service accounts, secure the EKS endpoint, handle node auto-scaling, and design for multi-AZ resilience. Because running Kubernetes in production demands many “day-2” considerations (upgrades, drift, monitoring, incident response), the guide provides practical advice beyond simple cluster provisioning. -
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DLRM
An implementation of a deep learning recommendation model (DLRM)
...The architecture combines dense (MLP) and sparse (embedding) branches, then interacts features via dot product or feature interactions before passing through further dense layers to predict click-through, ranking scores, or conversion probabilities. The implementation is optimized for performance at scale, supporting multi-GPU and multi-node execution, quantization, embedding partitioning, and pipelined I/O to feed huge embeddings efficiently. It includes data loaders for standard benchmarks (like Criteo), training scripts, evaluation tools, and capabilities like mixed precision, gradient compression, and memory fusion to maximize throughput. -
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amrlib
A python library that makes AMR parsing, generation and visualization
...Sentence to Graph alignment routines FAA_Aligner (Fast_Align Algorithm), based on the ISI aligner code detailed in this paper. RBW_Aligner (Rule Based Word) for a simple, single token to single node alignment. -
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fairseq2
FAIR Sequence Modeling Toolkit 2
...Unlike the original fairseq—which evolved into a large, monolithic codebase—fairseq2 introduces a clean, plugin-oriented architecture designed for long-term maintainability and rapid experimentation. It supports multi-GPU and multi-node distributed training using DDP, FSDP, and tensor parallelism, capable of scaling up to 70B+ parameter models. The framework integrates seamlessly with PyTorch 2.x features such as torch.compile, Fully Sharded Data Parallel (FSDP), and modern configuration management. -
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TorchRec
Pytorch domain library for recommendation systems
...It allows authors to train models with large embedding tables sharded across many GPUs. Parallelism primitives that enable easy authoring of large, performant multi-device/multi-node models using hybrid data-parallelism/model-parallelism. The TorchRec sharder can shard embedding tables with different sharding strategies including data-parallel, table-wise, row-wise, table-wise-row-wise, and column-wise sharding. The TorchRec planner can automatically generate optimized sharding plans for models. Pipelined training overlaps dataloading device transfer (copy to GPU), inter-device communications (input_dist), and computation (forward, backward) for increased performance. ... -
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Agents 2.0
An Open-source Framework for Data-centric Language Agents
...The project introduces a concept known as agent symbolic learning, which treats an agent pipeline similarly to a neural network computational graph. In this framework, each node in the pipeline represents a step in the reasoning or action process, while prompts and tools act as adjustable parameters analogous to neural network weights. During training, the system performs a forward execution where the agent completes a task and records the trajectory of prompts, outputs, and tool usage. A prompt-based loss function is then applied to evaluate the quality of the outcome, generating language-based gradients that guide improvements to the agent pipeline. -
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Matrix
Multi-Agent daTa geneRation Infra and eXperimentation framework
Matrix is a distributed, large-scale engine for multi-agent synthetic data generation and experiments: it provides the infrastructure to run thousands of “agentic” workflows concurrently (e.g. multiple LLMs interacting, reasoning, generating content, data-processing pipelines) by leveraging distributed computing (like Ray + cluster management). The idea is to treat data generation as a “data-to-data” transformation: each input item defines a task, and the runtime orchestrates asynchronous,... -
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NVIDIA NeMo Framework
Scalable generative AI framework built for researchers and developers
...It provides collections of domain-specific modules and reference implementations that make it easier to pre-train, fine-tune, and deploy very large models on multi-GPU and multi-node infrastructure. NeMo 2.0 introduces a Python-based configuration system, replacing YAML with more flexible, programmable configs that can be versioned and composed for different experiments. The framework builds on PyTorch Lightning–style modular abstractions, so training scripts are composed from reusable components for data loading, models, optimizers, and schedulers, which simplifies experimentation and adaptation. ... -
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Ray
A unified framework for scalable computing
Modern workloads like deep learning and hyperparameter tuning are compute-intensive and require distributed or parallel execution. Ray makes it effortless to parallelize single machine code — go from a single CPU to multi-core, multi-GPU or multi-node with minimal code changes. Accelerate your PyTorch and Tensorflow workload with a more resource-efficient and flexible distributed execution framework powered by Ray. Accelerate your hyperparameter search workloads with Ray Tune. Find the best model and reduce training costs by using the latest optimization algorithms. Deploy your machine learning models at scale with Ray Serve, a Python-first and framework agnostic model serving framework. ... -
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Tencent Cloud Code Analysis
Static code analysis
...Obtain the Tencent Cloud code analysis platform by deploying TCA Server and Web, and complete the creation of related projects on the platform. After the project is created, you can deploy and configure the Tencent Cloud code analysis client to perform code analysis locally or as an online resident node. Before starting your first code analysis project, you need to deploy the Tencent Cloud Code Analysis client locally. After completing the project configuration on the client, you can start your first code analysis project and view your analysis results. -
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ComfyUI-LivePortraitKJ
ComfyUI nodes for LivePortrait
...By leveraging diffusion and motion transfer techniques, it produces smooth and coherent animations. Overall, it provides an accessible way to generate portrait animations within a node-based pipeline. -
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FlowBench
Network stress testing & monitoring tool with legal compliance
NetPulse is a Windows app for network stress testing and performance monitoring, built with Python + PySide6. Features: - Stress Test: HTTP/HTTPS/TCP/UDP/ICMP; live QPS, latency percentiles, traffic stats - Collaborative Testing: invite-code based host/node modes; LAN direct or MQTT relay - Real-time monitoring of CPU/memory/network - Plugin System: built-in marketplace, one-click install/publish, extend with your own plugins - Dark/light theme, custom theme color, Chinese-English UI Compliance: per-target authorization, token-bucket rate limiting, audit logging. For authorized testing only — unauthorized stress testing is illegal. ... -
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Datahosting ipfs kubo-cluster
Managed IPFS Kubo pinning with IPFS Cluster replication
This project provides an open-source setup for IPFS Kubo (public and private pinning) combined with IPFS Cluster replication, designed for reliable, production-ready decentralized storage. It is suitable for developers, infrastructure operators, and Web3 projects that need predictable IPFS availability without maintaining complex node infrastructure. The system supports multiple retention plans for IPFS Kubo pinning, allowing users to choose how long data remains pinned, with transparent pay-per-GB prepaid pricing. Retention options include short-term and long-term storage, making it suitable for websites, datasets, backups, and distributed applications. For higher availability, IPFS Cluster replication is available with 1, 2, or 3 replicas, enabling redundancy across nodes and improved resilience against node failure. ... -
16
Cryptocheck
Monitors balances of your cryptocurrency addresses
...You no longer need to access all your wallets with passwords to simply just check that your money are still there. Cryptocheck also provides a simple profit calculation and history charts mapping your portfolio history. And there is also a server node available! It continuously monitors balances, records history data and sends all the data to your Cryptocheck desktop application. Supported cryptocurrencies: https://sourceforge.net/p/cryptocheck/wiki/Home/#supported-cryptocurrencies For more details about Cryptocheck and how to use it, see wiki: https://sourceforge.net/p/cryptocheck/wiki I am open to add other cryptocurrencies on your request. -
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Astrape
Optical-packet node transceiver frequency allocation
In an optical network scenario which consists of multiple nodes (whiteboxes) at its edges and ROADMs in-between, the coherent transceiver average laser configuration time is improved. The process is evaluated according to a testbed setup. This is facilitated in the appropriate lab equipment (or via simulation when required). For that purpose, a software agent (Netconf server) residing at the whiteboxes, is developed receiving input from the Software-Defined Networking (SDN) packet... -
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FreeTAKServer
Situational Awareness Server compatible with TAK clients
FTS is a Python3 implementation of a TAK Server for devices like ATAK, WinTAK, and ITAK, it is cross-platform and runs from a multi-node installation on AWS down to the Android edition. It's free and open source (released under the Eclipse Public License. FTS allows you to connect ATAK clients to share geo-information, to chat with all the connected clients, exchange files and more. It intends to support all the major use cases of the original TAK server. -
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ComfyUI InstantID ZHO
Unofficial implementation of InstantID for ComfyUI
...It adds custom nodes for loading SDXL base models, InsightFace, ID ControlNet, and the InstantID IP-Adapter. Base models can be loaded locally or downloaded from Hugging Face. The generation node accepts a face reference and can optionally use a pose reference focused around the face. Users can tune IP-Adapter strength, ControlNet conditioning, steps, guidance, seed, and face enhancement. Prompt styling supports positive and negative prompts plus multiple preset styles, while InsightFace can run on CUDA or CPU. -
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AIConfig
AIConfig is a config-based framework to build generative AI apps
...AIConfig supports multiple model providers and modalities, enabling developers to experiment with different models without rewriting application logic. The configuration format is JSON-serializable and integrates with tools such as Python and Node SDKs, allowing the same configuration file to be used across multiple environments. -
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Bufferstack.IO IIoT-Gateway
IIoT Gateway for interfacing industrial,home automation applications
This is Bufferstack. IO IIoT Gateway based on LTS stable software base which allows one to develop, deploy and host IOT, IIoT based applications using NodeJS, Python, influxdb, mosquitto mqtt broker. This is live+install CD, and for better experience in using it, please install it on your HDD/VM/Cloud -
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Bert-VITS2
VITS2 backbone with multilingual-bert
...The repository includes everything needed to train, fine-tune, and run the model, from configuration files to preprocessing scripts, spectrogram utilities, and training entrypoints for multi-GPU and multi-node setups. It provides emotional modeling through “emo embeddings,” allowing voices to be conditioned on different affective states during synthesis. Releases include optimizations for Japanese and English alignment, expanded training data, spec caching and pre-generation tools, as well as ONNX export for more lightweight inference deployments. -
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Aviary
Ray Aviary - evaluate multiple LLMs easily
...Providing an extensive suite of pre-configured open source LLMs, with defaults that work out of the box. Supporting Transformer models hosted on Hugging Face Hub or present on local disk. Aviary has native support for autoscaling and multi-node deployments thanks to Ray and Ray Serve. Aviary can scale to zero and create new model replicas (each composed of multiple GPU workers) in response to demand. Ray ensures that the orchestration and resource management is handled automatically. Aviary is able to support hundreds of replicas and clusters of hundreds of nodes, deployed either in the cloud or on-prem. -
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django-sspanel
Diango shadowsocks
Shadowsocks panel developed with diango. Smart subscription system , support ss/clash/clash premium version. Deep integration with transit tunnels , convenient and fast construction of transit tunnels d7e4380-6532-* Backend supports common protocols. Registration adopts the invitation system to bid farewell to bad users. Unified and perfect background management interface. Perfect commodity purchase logic. Alipay face-to-face payment module. Invitation rebate system. -
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InternLM
Official release of InternLM series
...The broader InternLM ecosystem also includes training tooling and guidance aimed at making fine-tuning and adaptation more accessible across hardware setups, including smaller single-GPU environments and larger multi-node configurations.
