Search Results for "transfer function model"
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138 projects for "transfer function model" with 1 filter applied:
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Large Concept Model
Language modeling in a sentence representation space
Large Concept Model is a research codebase centered on concept-centric representation learning at scale, aiming to capture shared structure across many categories and modalities. It organizes training around concepts (rather than just raw labels), encouraging models to understand attributes, relations, and compositional structure that transfer across tasks. -
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Mooncake
Mooncake is the serving platform for Kimi
Mooncake is an open-source infrastructure platform designed to optimize large language model serving by focusing on efficient management and transfer of model data and KV cache. The platform was originally developed as part of the serving infrastructure for the Kimi large language model system. Its architecture centers on a high-performance transfer engine that provides unified data transfer across different storage and networking technologies. ... -
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Cactus Needle
26m function call model that runs on incredibly small devices
Needle is an experimental 26-million-parameter function-calling model designed to run on extremely small devices such as phones, watches, glasses, and low-power personal AI hardware. It is based on a Simple Attention Network architecture and was distilled from a much larger model to focus on fast, compact tool-use behavior. The project provides open weights, training details, dataset generation resources, and a playground for testing the model with custom tools. ... -
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ControlSystems.jl
A Control Systems Toolbox for Julia
ControlSystems.jl is a Julia toolbox for control systems design and analysis, offering models in transfer-function and state-space representations, enabling construction of complex systems, simulation in time and frequency domains, and performance/stability evaluation. This toolbox works similar to that of other major computer-aided control systems design (CACSD) toolboxes. Systems can be created in either a transfer function or a state space representation. ... -
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spacy-transformers
Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy
spaCy supports a number of transfer and multi-task learning workflows that can often help improve your pipeline’s efficiency or accuracy. Transfer learning refers to techniques such as word vector tables and language model pretraining. These techniques can be used to import knowledge from raw text into your pipeline, so that your models are able to generalize better from your annotated examples. -
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Ziggy
Use your Laravel routes in JavaScript
Ziggy provides a JavaScript route() function that works like Laravel's, making it a breeze to use your named Laravel routes in JavaScript. Ziggy supports Laravel's route-model binding, and can even recognize custom route key names. If you pass route() a JavaScript object as a route parameter, Ziggy will use the registered route-model binding keys for that route to find the correct parameter value inside the object. -
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gemini-web2api
Convert Google Gemini web into OpenAI-compatible API
...It is designed to let OpenAI-style clients connect to Gemini-like models through routes such as chat completions, models, responses, and native Gemini-compatible endpoints. The project can run as a simple local server and uses a mostly single-file design with an optional dependency for streaming. It supports model aliases for Flash, Thinking, Pro-style routing, Auto, and Lite variants. The tool also includes optional API keys, function calling, SSE streaming, web search access, Docker deployment, and client examples for OpenAI SDK-style usage. It is useful for developers who want local experimentation with OpenAI-compatible tooling while routing requests through Gemini web behavior. -
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MetaCLIP
ICLR2024 Spotlight: curation/training code, metadata, distribution
...It includes utilities to fine-tune vision-language embeddings, compute prompt or adapter updates, and benchmark across transfer and retention metrics. MetaCLIP is especially suited for real-world settings where a model must continuously incorporate new visual categories or domains over time. -
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ComfyUI IPAdapter plus
ComfyUI reference implementation for IPAdapter models
ComfyUI_IPAdapter_plus is a ComfyUI extension that adds a reference implementation for IPAdapter models. It focuses on image-to-image conditioning, letting a reference image guide the subject, style, or composition of a new generation. The project treats IPAdapter like a one-image LoRA, making it useful when users want visual influence without full model training. It includes example workflows that cover the main IPAdapter functions and help users build practical ComfyUI graphs. The... -
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Keiyoushi Extensions
Extension repository for Mihon and variants
Keiyoushi Extensions is an open-source repository that provides a large collection of third-party content source extensions designed primarily for manga reading applications such as Tachiyomi-based clients. These extensions function as connectors that allow users to browse, search, and read content from a wide range of external websites within a unified app interface. The project is structured to support modular installation, enabling users to selectively add or remove sources based on their... -
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DINOv2
PyTorch code and models for the DINOv2 self-supervised learning
...It builds on the DINO idea of student–teacher distillation and adapts it to modern Vision Transformer backbones with a carefully tuned recipe for data augmentation, optimization, and multi-crop training. The core promise is that a single pretrained backbone can transfer well to many downstream tasks—from linear probing on classification to retrieval, detection, and segmentation—often requiring little or no fine-tuning. The repository includes code for training, evaluating, and feature extraction, with utilities to run k-NN or linear evaluation baselines to assess representation quality. Pretrained checkpoints cover multiple model sizes so practitioners can trade accuracy for speed and memory depending on their deployment constraints. -
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Ollama4j
A simple Java library for interacting with Ollama server
...It provides a clean and developer-friendly API that abstracts the underlying REST communication, allowing users to focus on building features rather than handling low-level networking details. The library supports a wide range of core capabilities, including chat-based interactions, text generation, embeddings, and model management, making it suitable for both simple applications and more advanced AI-driven systems. It integrates seamlessly into Java ecosystems through Maven or Gradle dependencies, and it works with standard Java environments starting from JDK 11 and above. Ollama4j also includes support for advanced features such as tool or function calling, enabling models to interact with external systems and execute more complex workflows. -
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Ollama-rs
A simple and easy-to-use library for interacting with the Ollama API
...It follows the official Ollama API closely, ensuring compatibility while offering an idiomatic Rust experience with strong typing and asynchronous execution. The library supports a wide range of operations, including text generation, chat interactions, embeddings, and model management, making it suitable for both simple applications and more advanced AI workflows. It includes streaming capabilities for real-time output, allowing developers to process responses incrementally rather than waiting for full completions. The project also introduces support for tool calling and custom function integration, enabling more dynamic and agent-like behavior within applications. -
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ACI.dev
Open platform connecting AI agents to tools via unified MCP server
...ACI provides intent-aware tool access, meaning agents can dynamically discover and use tools based on context rather than rigid configurations. It supports both direct function calling and a unified Model Context Protocol (MCP) server, offering flexibility in how integrations are exposed to AI systems. ACI also includes multi-tenant authentication and permission controls, ensuring that tool usage is secure and scoped appropriately for different users and agents. Additionally, it is framework-agnostic, making it compatible with various large language model setups and agent architectures. -
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Ollama-Laravel Package
Ollama-Laravel is a Laravel package providing seamless integration
Ollama-Laravel Package is a PHP package designed to integrate local large language models into Laravel applications through a clean and idiomatic interface. It abstracts the Ollama API into a developer-friendly facade, allowing Laravel developers to interact with models using familiar patterns such as service containers, configuration files, and fluent method chaining. The package supports a wide range of AI capabilities including text generation, chat-based interactions, embeddings, and... -
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Skywork-R1V4
Skywork-R1V is an advanced multimodal AI model series
Skywork-R1V is an open-source multimodal reasoning model designed to extend the capabilities of large language models into vision-language tasks that require complex logical reasoning. The project introduces a model architecture that transfers the reasoning abilities of advanced text-based models into visual domains so the system can interpret images and perform multi-step reasoning about them. Instead of retraining both language and vision models from scratch, the framework uses a... -
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OpenCTI
Open Cyber Threat Intelligence Platform
OpenCTI is a comprehensive open-source cyber threat intelligence platform designed to help organizations collect, structure, analyze, and share information about cyber threats. It provides a modern web application backed by a GraphQL API and a data model aligned with the STIX2 standard to ensure interoperability across the threat intelligence ecosystem. The platform enables teams to correlate technical indicators such as observables and TTPs with higher-level context like attribution and victimology, creating a unified intelligence knowledge base. OpenCTI is built to integrate with external tools including MISP, TheHive, and MITRE ATT&CK, allowing it to function as a central intelligence hub in security operations. ... -
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Chat UI
The open source codebase powering HuggingChat
Hugging Face Chat UI is an open-source web interface designed for interacting with large language models through a modern conversational interface. The project serves as the codebase behind HuggingChat and can be deployed locally or on cloud infrastructure to create customizable AI chat applications. Built with modern web technologies such as SvelteKit and backed by MongoDB for persistence, the interface provides a responsive environment for multi-turn conversations, file handling, and... -
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4M
4M: Massively Multimodal Masked Modeling
4M is a training framework for “any-to-any” vision foundation models that uses tokenization and masking to scale across many modalities and tasks. The same model family can classify, segment, detect, caption, and even generate images, with a single interface for both discriminative and generative use. The repository releases code and models for multiple variants (e.g., 4M-7 and 4M-21), emphasizing transfer to unseen tasks and modalities. Training/inference configs and issues discuss things like depth tokenizers, input masks for generation, and CUDA build questions, signaling active research iteration. ... -
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YuE
Open source AI model for generating full songs from lyrics prompts
YuE is an open source project that provides a foundation model designed for full-song music generation using artificial intelligence. It focuses on transforming text inputs such as lyrics and genre prompts into complete musical compositions that include both vocal and instrumental tracks. Unlike many shorter audio generators, the model is capable of producing songs that last several minutes while maintaining coherent musical structure and alignment with the provided lyrics. YuE introduces a... -
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Functions Framework for Node.js
FaaS (Function as a service) framework for writing portable Node.js
Functions Framework for Node.js is a lightweight runtime library that allows developers to write and run portable serverless functions locally or in cloud environments using standard Node.js. It provides a consistent execution model that mimics Google Cloud Functions, enabling developers to build, test, and debug functions on their local machine before deploying them to production. The framework supports multiple function signature types, including HTTP-based functions and event-driven functions, and automatically parses incoming request payloads into structured objects that can be easily consumed by application logic. ... -
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Outlines
Structured Outputs
Outlines is a Python library for making language models generate predictable, structured outputs. Instead of repairing malformed responses afterward, it constrains generation to match a requested type or format. Developers can require predefined choices, primitive Python types, Pydantic models, JSON schemas, regular expressions, function signatures, or custom grammars. The same interface works with local models, inference servers, and hosted APIs from several providers. Supported... -
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DeepSeek Engineer v2
A powerful coding assistant application
DeepSeek Engineer v2 is an AI-powered coding assistant built around DeepSeek models and an interactive terminal workflow. It lets developers discuss code, request analysis, and perform project work through natural language. Version 2.0 focuses on native function calling instead of rigid structured JSON responses. The assistant can read files, read multiple files, create files, create multiple files, and edit specific snippets when needed. It includes safeguards such as path validation,... -
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Reaktive
Kotlin multi-platform implementation of Reactive Extensions
Kotlin multiplatform implementation of Reactive Extensions. There are a number of modules published to Maven Central. This functionality is provided by the coroutines-interop module. Reaktive provides an easy way to manage subscriptions: DisposableScope. Reaktive provides Plugin API, something similar to RxJava plugins. The Plugin API provides a way to decorate Reaktive sources. A plugin should implement the ReaktivePlugin interface, and can be registered using the registerReaktivePlugin... -
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Casibase
Open-source enterprise-level AI knowledge base and MCP
Casibase is an open-source AI cloud platform designed to function as an enterprise knowledge base, container management system, and collaboration environment for AI-driven applications. The project combines knowledge management, messaging, and forum features with large language model integration to create an interactive platform for storing and querying domain-specific knowledge. Built with a separated frontend and backend architecture, Casibase provides a web-based administrative interface and supports high concurrency for enterprise environments. ...
