Search Results for "transfer function model" - Page 3
Sort By:
138 projects for "transfer function model" with 1 filter applied:
-
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
-
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
1
StyleTTS 2
Towards Human-Level Text-to-Speech through Style Diffusion
StyleTTS2 is a state-of-the-art text-to-speech system that aims for human-level naturalness by combining style diffusion, adversarial training, and large speech language models. It extends the original StyleTTS idea by introducing a style diffusion model that can sample rich, realistic speaking styles conditioned on reference speech, allowing highly expressive and diverse prosody. The architecture uses a two-stage training process and leverages an auxiliary speech language model to guide generation toward more natural and coherent utterances. StyleTTS2 supports both single-speaker and multi-speaker configurations, with the ability to sample or transfer styles from reference audio, making it powerful for expressive TTS and character voices. ... -
2
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. ... -
3
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. ... -
4
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. -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
-
5
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... -
6
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. ... -
7
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. ... -
8
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... -
9
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. ... -
$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.
-
10
Reinforcement Learning Methods
Simple Reinforcement learning tutorials
Reinforcement-Learning-with-TensorFlow is an educational repository that walks through key reinforcement learning algorithms implemented in TensorFlow. It provides clear code examples for foundational techniques like Q-learning, policy gradients, deep Q-networks, actor-critic methods, and value function approximation within familiar simulation environments. Each algorithm is structured with readable code, explanatory comments, and corresponding environment interaction loops so learners can easily trace how actions, rewards, and model updates connect. The project also includes demo scripts that visualize learning curves and allow students to observe policy improvement over training iterations. ... -
11
Deep Learning 500 Questions
500 Questions on Deep Learning using a question-and-answer format
...Later chapters explore classic neural network structures such as CNNs, RNNs, and GANs, as well as key applications in computer vision like object detection and image segmentation. The resource also delves into optimization methods, including transfer learning, network architecture design, hyperparameter tuning, model compression, and acceleration techniques. -
12
ReinventCommunity
Jupyter Notebook tutorials for REINVENT 3.2
This repository is a collection of useful jupyter notebooks, code snippets and example JSON files illustrating the use of Reinvent 3.2. -
13
Machine Learning & Deep Learning
machine learning and deep learning tutorials, articles
Machine Learning & Deep Learning Tutorials is an open-source repository that provides practical tutorials demonstrating how to implement machine learning and deep learning models using popular frameworks such as TensorFlow and PyTorch. The project focuses on helping learners understand machine learning through hands-on coding examples rather than purely theoretical explanations. Each tutorial walks through the process of building and training models for tasks such as image classification,... -
14
XLM (Cross-lingual Language Model)
PyTorch original implementation of Cross-lingual Language Model
XLM (Cross-lingual Language Model) is a family of multilingual pretraining methods that align representations across languages to enable strong zero-shot transfer. It popularized objectives like Masked Language Modeling (MLM) across many languages and Translation Language Modeling (TLM) that jointly trains on parallel sentence pairs to tighten cross-lingual alignment. -
15
ml-design-patterns
Source code accompanying O'Reilly book: Machine Learning Design
The ml-design-patterns repository contains the source code and examples that accompany the book “Machine Learning Design Patterns,” providing practical implementations of reusable solutions for common challenges in machine learning systems. It organizes patterns into categories such as data representation, problem framing, and model training, helping practitioners understand how to structure ML pipelines effectively. The repository includes implementations of techniques like feature hashing, embeddings, feature crosses, and multimodal inputs, which are essential for handling diverse data types. It also covers strategies for improving model performance and robustness, including transfer learning, checkpointing, ensemble methods, and rebalancing techniques for imbalanced datasets. ... -
16
3 Rs of Software Architecture
A guide on how to write readable, reusable, and refactorable software
This guide aims to help software developers think more clearly about how to build systems that are not only functional today but maintainable into the future. It focuses on three architectural “ilities”: readability, reusability, and refactorability, presenting them in a hierarchical framework so developers can evaluate and improve their code and system design. The project uses a simple shopping-cart application written in JavaScript and React/Redux to illustrate how code evolves from “bad”... -
17
Tensorflow 2017 Tutorials
Tensorflow tutorial from basic to hard
Tensorflow 2017 Tutorials is a structured set of tutorials that introduce developers to TensorFlow, starting with basic neural network constructs and progressing to sophisticated model architectures and training techniques. This repository covers essential building blocks like sessions (for older TF versions), placeholders, variables, activation functions, and optimizers, before guiding learners through building end-to-end models for regression, classification, and data pipelines. Beyond the basics, the project includes examples of convolutional neural networks, recurrent networks, autoencoders, reinforcement learning, generative adversarial networks, and transfer learning workflows. ... -
18
TensorFlow 2.0 Tutorials
TensorFlow 2.x version's Tutorials and Examples
...These examples cover a wide range of topics including convolutional neural networks, recurrent neural networks, generative adversarial networks, autoencoders, and transformer-based models such as GPT and BERT. Each section of the repository includes runnable code and structured experiments designed to illustrate how different architectures and algorithms function in real applications. The tutorials use well-known benchmark datasets such as MNIST, CIFAR, and Fashion-MNIST to demonstrate practical model training and evaluation workflows. -
19
SentEval
A python tool for evaluating the quality of sentence embeddings
...Because the interface is minimal, researchers can plug in encoders from any framework or language model and obtain a broad evaluation with little glue code. SentEval helped establish common baselines and reporting conventions in the sentence-representation community, reducing friction when comparing new methods. -
20
StarGAN
Official PyTorch Implementation
StarGAN is an implementation of the Star Generative Adversarial Network, a model designed for multi-domain image-to-image translation using a single unified GAN architecture. Unlike earlier GAN approaches that required separate models for each domain pair, StarGAN enables flexible attribute transfer across multiple domains within one network, significantly improving efficiency and scalability. The repository includes full training and inference pipelines for tasks such as facial attribute manipulation and style transfer. ... -
21
The Neural Process Family
This repository contains notebook implementations
...Implementations rely only on standard dependencies such as NumPy, TensorFlow, and Matplotlib, and provide visualizations of model performance. -
22
Laravel Searchable
A php trait to search laravel models
Searchable is a trait for Laravel 4.2+ and Laravel 5.0 that adds a simple search function to Eloquent Models. Searchable allows you to perform searches in a table giving priorities to each field for the table and its relations. This is not optimized for big searches, but sometimes you just need to make it simple (Although it is not slow). By default, multi-word search terms are split and Searchable searches for each word individually. Relevance plays a role in prioritizing matches that match... -
23
Python Milter
Python API for Sendmail Milters.
Python API for Sendmail Milters. Related modules provide features such as content filtering, SPF, and reputation tracking. Changes are posted first to https://github.com/sdgathman/pymilter and related repos. -
24
RecNN
Reinforced Recommendation toolkit built around pytorch 1.7
This is my school project. It focuses on Reinforcement Learning for personalized news recommendation. The main distinction is that it tries to solve online off-policy learning with dynamically generated item embeddings. I want to create a library with SOTA algorithms for reinforcement learning recommendation, providing the level of abstraction you like. -
25
Incremental DOM
An in-place DOM diffing library
Incremental DOM is a lightweight library for building DOM trees by issuing imperative update instructions, avoiding heavyweight virtual DOM diffing at runtime. Instead of creating and diffing large object graphs, templates compile to a sequence of function calls that “patch” the live DOM in place. This model eliminates allocations associated with virtual trees and allows updates to be streamed directly to the DOM, which can improve memory usage and reduce GC pressure. It integrates naturally with template compilers (such as those that generate calls from HTML-like markup) but can also be used by hand for fine-tuned rendering. ...
