Search Results for "transfer function model" - Page 6
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Showing 297 open source projects for "transfer function model"
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Qwen-Audio
Chat & pretrained large audio language model proposed by Alibaba Cloud
Qwen-Audio is a large audio-language model developed by Alibaba Cloud, built to accept various types of audio input (speech, natural sounds, music, singing) along with text input, and output text. There is also an instruction-tuned version called Qwen-Audio-Chat which supports conversational interaction (multi-round), audio + text input, creative tasks and reasoning over audio. It uses multi-task training over many different audio tasks (30+), and achieves strong multi-benchmarks performance... -
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TensorFlow Hub
A library for transfer learning by reusing parts of TensorFlow models
...The project enables developers to integrate high-quality models into their applications without needing to train them from scratch. Through TensorFlow Hub, researchers and practitioners can share reusable model components such as image classifiers, text embedding models, and object detection networks. These models can be loaded directly into TensorFlow pipelines and fine-tuned for new tasks using transfer learning techniques. The repository supports contributions from the community, allowing developers to submit models that become available for use by other machine learning practitioners. ... -
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Functionary
Chat language model that can use tools and interpret the results
Functionary is an open-source large language model specifically designed for interpreting and executing structured functions or external tools within conversational AI systems. The model extends traditional chat-based language models by enabling them to determine when external functions should be called and how to extract the necessary parameters from natural language input. Function definitions are typically provided in JSON schema format, allowing the model to generate structured function calls compatible with modern tool-calling interfaces used in AI applications. ... -
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Django Notebook
Django + shell_plus + Jupyter notebooks made easy
Django + shell_plus + Jupyter notebooks made easy. A Jupyter notebook with access to objects from the Django ORM is a powerful tool to introspect data and run ad-hoc queries. Built-in integration with the imported objects from django-extensions shell_plus. Saves the state between sessions so you don't need to remember what you did. Inheritance diagrams on any object, including ORM models. -
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D3
Bring data to life with SVG, Canvas and HTML
D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS. D3’s emphasis on web standards gives you the full capabilities of modern browsers without tying yourself to a proprietary framework, combining powerful visualization components and a data-driven approach to DOM manipulation. D3 allows you to bind arbitrary data to a Document Object Model (DOM), and then apply data-driven transformations to the document. For... -
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ZX Spectrum Bulk Data Transfer - esxdos
ZX Spectrum bulk data transfer via EAR port.
A set of tools for transferring arbitrary files (of arbitrary lengh, up to 1Gb) to ZX Spectrum machine via tape input (EAR). No additional hardware required. t2esx utility is intended to transfer data to the ZX Spectrum via the EAR port without any additional hardware. If you have the means to play back TAP files, t2esx allows you to transfer any arbitrary amount of raw data (theoretical upper limit – 1G). Utility provided in two flavours – “regular” 48k programme and the esxdos dot command. There are no other restrictions, utility uses standard ROM routine for loading data blocks from the audio input port, so it works on any Spectrum model. ... -
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Ailice
AIlice is a fully autonomous, general-purpose AI agent
AIlice is an open-source autonomous AI agent framework built to function as a general-purpose assistant that can plan, decompose, and execute complex tasks through a structured multi-agent architecture. The project presents itself as a standalone assistant powered by open-source language models, with an internal design that treats user requests almost like executable programs rather than simple chat prompts. Its core IACT architecture allows the system to break large goals into smaller... -
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Transmittable ThreadLocal
Provides an enhanced InheritableThreadLocal
TransmittableThreadLocal (TTL), the missing Java™ std lib(simple & 0-dependency) for framework/middleware, provide an enhanced InheritableThreadLocal that transmits values between threads even using thread pooling components. In the case of using thread pools and other execution components that will pool multiple threads, the ThreadLocalvalue transfer function is provided to solve the problem of context transfer during asynchronous execution. A Javastandard library should provide standard capabilities for framework/middleware facility development. ThreadLocalThe demand scenario is TransmittableThreadLocalthe potential demand scenario. If your business needs to "pass ThreadLocalvalues in the case of using thread pools and other execution components that will pool multiple threads ", it is the TransmittableThreadLocaltarget scenario. -
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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 ship with Sonnet, making it quite powerful and yet simple at the same time. Users are also encouraged to build their own modules. ... -
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Bayesian Julia
Bayesian Statistics using Julia and Turing
Bayesian statistics is an approach to inferential statistics based on Bayes' theorem, where available knowledge about parameters in a statistical model is updated with the information in observed data. The background knowledge is expressed as a prior distribution and combined with observational data in the form of a likelihood function to determine the posterior distribution. The posterior can also be used for making predictions about future events. Bayesian statistics is a departure from classical inferential statistics that prohibits probability statements about parameters and is based on asymptotically sampling infinite samples from a theoretical population and finding parameter values that maximize the likelihood function. ... -
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Shap-E
Generate 3D objects conditioned on text or images
The shap-e repository provides the official code and model release for Shap-E, a conditional generative model designed to produce 3D assets (implicit functions, meshes, neural radiance fields) from text or image prompts. The model is built with a two-stage architecture: first an encoder that maps existing 3D assets into parameterizations of implicit functions, and then a conditional diffusion model trained on those parameterizations to generate new assets. Because it works at the level of... -
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OpenAI-Java
OpenAI Api Client in Java
...For complex use cases (e.g. structured outputs, function calling), it provides schema support, JSON annotations, and schema validation. -
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TextGen
textgen, Text Generation models
Implementation of Text Generation models. textgen implements a variety of text generation models, including UDA, GPT2, Seq2Seq, BART, T5, SongNet and other models, out of the box. UDA, non-core word replacement. EDA, simple data augmentation technique: similar words, synonym replacement, random word insertion, deletion, replacement. This project refers to Google's UDA (non-core word replacement) algorithm and EDA algorithm, based on TF-IDF to replace some unimportant words in sentences with... -
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CSAw - NLP for low-resource languages
CSAw is an NLP framework for low-resource languages
CSAw is an NLP framework for low-resource languages with a focus on machine translation. The primary goal is to build language models automatically from bilingual text (e.g., front and back translations) using a deep transfer rule-based approach. The core of this strategy is the Concept Specification and Abstraction semantic representation which is specially designed with machine translation in mind. See the preprint article here: https://arxiv.org/abs/1807.02226 The current framework includes transduction algorithms (i.e., from text to semantic representation and back again) and some components needed for automatic language model building (lexical alignment and grammar rule generation). ... -
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ChatHN
Chat with Hacker News using natural language
ChatHN is an open-source chatbot that lets users explore Hacker News through natural-language questions. It connects an OpenAI model to the official Hacker News API through function calling, allowing the model to retrieve live structured data when needed. Built-in functions can fetch top stories, open a specific story, include leading comments, and prepare the current top discussion for summarization. Responses are streamed through the Vercel AI SDK so the interface can display generated text progressively. ... -
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GraphQL Voyager
Represent any GraphQL API as an interactive graph
Represent any GraphQL API as an interactive graph. It's time to finally see the graph behind GraphQL. You can also explore number of public GraphQL APIs from our list. With graphql-voyager you can visually explore your GraphQL API as an interactive graph. This is a great tool when designing or discussing your data model. It includes multiple example GraphQL schemas and also allows you to connect it to your own GraphQL endpoint. What are you waiting for, explore your API! Quick navigation on... -
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Project: Olympus
An Arduino-based Altitude and IMU Payload for Model Rocketry
Project: Olympus is an engineering project that utilizes an Arduino Nano microcontroller to create an electronic payload that records altitude, g-forces experienced by the rocket, as well as roll rate. Included with the code is a 132 page Project Manual that takes you through the design and construction of the electronic payload. It also includes sections on the construction of the Estes Olympus rocket. A detailed code review of each section of code is included. We take a detailed look... -
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ParlAI
A framework for training and evaluating AI models
ParlAI is a comprehensive research platform for building, training, and evaluating dialogue agents across a wide variety of tasks and datasets. It provides a unified interface—agents, teachers, and worlds—so the same model can be trained on multi-turn chit-chat, question answering, task-oriented dialogue, retrieval, or safety-focused datasets without changing core code. The library integrates tightly with PyTorch and supports both generative and retrieval-augmented models, along with... -
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smclarify
Fairness aware machine learning. Bias detection and mitigation
...A facet can have value(s) that designates that sample as "sensitive". Bias detection and mitigation for datasets and models. The label is a column or feature which is the target for training a machine learning model. The label can have value(s) that designates that sample as having a "positive" outcome. A bias measure is a function that returns a bias metric. A bias metric is a numerical value indicating the level of bias detected as determined by a particular bias measure. A collection of bias metrics for a given dataset or a combination of a dataset and model. -
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Nunjucks
A rich and powerful templating language for JavaScript
A powerful templating engine with inheritance, asynchronous control, and more (jinja2 inspired). You've been looking for a more sophisticated templating engine for JavaScript. Here it is. Rich Powerful language with block inheritance, autoescaping, macros, asynchronous control, and more. Heavily inspired by jinja2. Fast & Lean High-performant. Small 8K gzipped runtime with precompiled templates in the browser. Crazy extensible with custom filters and extensions. Everywhere available in node... -
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PIFuHD
High-Resolution 3D Human Digitization from A Single Image
PIFuHD (Pixel-Aligned Implicit Function for 3D human reconstruction at high resolution) is a method and codebase to reconstruct high-fidelity 3D human meshes from a single image. It extends prior PIFu work by increasing resolution and detail, enabling fine geometry in cloth folds, hair, and subtle surface features. The method operates by learning an implicit occupancy / surface function conditioned on the image and camera projection; at inference time it queries dense points to reconstruct a mesh via marching cubes. ... -
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Hippo4j
Powerful dynamic thread pool framework with monitoring/alarm functions
Dynamically observable thread pool framework to improve online operation guarantee capabilities for business systems. Dynamically change thread pool parameters when the application is running, including not limited to core, maximum thread, blocking queue size, and rejection strategy, etc., and support different node thread pool configuration differentiation under the application cluster. Buried when the application thread pool is running, it provides four alarm dimensions, such as... -
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o'scopepy
Oscilloscope using PC sound card and Python 3
...Tkinter is used for both GUIs and for creating a second event loop used for synchronizing workcell to workcell communication. Three classes, Hub, Requestify and Transceiver are used to implement the parallel programming model. Hub is used as the central communication facility. Requestify is used for function binding by Tkinter widgets command option and Transceiver is inherited by workcells for communication functions. This programming model makes it very easy to write highly interactive programs as demonstrated by this project with very easy addition of plugin tools. -
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Point-E
Point cloud diffusion for 3D model synthesis
point-e is the official repository for Point-E, a generative model developed by OpenAI that produces 3D point clouds from textual (or image) prompts. Its principal advantage is speed: it can generate 3D assets in just 1–2 minutes on a single GPU, which is significantly faster than many competing text-to-3D models. The model works via a two-stage diffusion approach: first, it uses a text → image diffusion network to produce a synthetic 2D view consistent with the prompt; then a second diffusion model converts that image into a 3D point cloud. ... -
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TextBox
A text generation library with pre-trained language models github.com
TextBox 2.0 is an up-to-date text generation library based on Python and PyTorch focusing on building a unified and standardized pipeline for applying pre-trained language models to text generation. From a task perspective, we consider 13 common text generation tasks such as translation, story generation, and style transfer, and their corresponding 83 widely-used datasets. From a model perspective, we incorporate 47 pre-trained language models/modules covering the categories of general, translation, Chinese, dialogue, controllable, distilled, prompting, and lightweight models (modules). From a training perspective, we support 4 pre-training objectives and 4 efficient and robust training strategies, such as distributed data parallel and efficient generation. ...
