Search Results for "pam-python" - Page 56
Sort By:
Showing 2055 open source projects for "pam-python"
View related business solutions-
Cloud tools for web scraping and data extractionAutomate web data collection with cloud tools that handle anti-bot measures, browser rendering, and data transformation out of the box. Extract content from any website, push to vector databases for RAG workflows, or pipe directly into your apps via API. Schedule runs, set up webhooks, and connect to your existing stack. Free tier available, then scale as you need to.
-
Atera all-in-one platform IT management software with AI agentsAtera’s AI agents don’t just assist, they act. From detection to resolution, they handle incidents and requests instantly, taking your IT management from automated to autonomous.
-
1
RLCard
Reinforcement Learning / AI Bots in Card (Poker) Games
RLCard is a toolkit for reinforcement learning research on card games. It includes several popular card games and focuses on learning algorithms for imperfect information games like poker and blackjack. -
2
bert4keras
Keras implement of transformers for humans
Our light reimplementation of bert for keras. A cleaner, lighter version of bert for keras. This is the keras version of the transformer model library re-implemented by the author and is committed to combining transformer and keras with as clean code as possible. The original intention of this project is for the convenience of modification and customization, so it may be updated frequently. Load the pre-trained weights of bert/roberta/albert for fine-tune. Implement the attention mask... -
3
Yukki Music Bot
Telegram Group Calls Streaming bot with some useful features
Yukki Music Bot is a Powerful Telegram Music+Video Bot written in Python using Pyrogram and Py-Tgcalls by which you can stream songs, video and even live streams in your group calls via various sources. -
4
CIPS-3D
3D-aware GANs based on NeRF (arXiv)
3D-aware GANs based on NeRF (arXiv). This repository contains the code of the paper, CIPS-3D: A 3D-Aware Generator of GANs Based on Conditionally-Independent Pixel Synthesis. The problem of mirror symmetry refers to the sudden change of the direction of the bangs near the yaw angle of pi/2. We propose to use an auxiliary discriminator to solve this problem. Note that in the initial stage of training, the auxiliary discriminator must dominate the generator more than the main discriminator... -
Grafana: The open and composable observability platformGrafana is the open source analytics & monitoring solution for every database.
-
5
NWT - Pytorch (wip)
Implementation of NWT, audio-to-video generation, in Pytorch
Implementation of NWT, audio-to-video generation, in Pytorch. The paper proposes a new discrete latent representation named Memcodes, which can be succinctly described as a type of multi-head hard-attention to learned memory (codebook) key/values. They claim the need for less codes and smaller codebook dimensions in order to achieve better reconstructions. -
6
Piano transcription
Task of transcribing piano recordings into MIDI files
Piano transcription is an open-source high-resolution piano transcription system by ByteDance that converts raw audio recordings of piano performance into symbolic MIDI files — detecting note onsets, offsets, pitch, velocity, and even pedal usage. The system is implemented in Python (PyTorch) and is capable of accurate transcription of polyphonic piano recordings, even with complex passages and pedal techniques, making it suitable for classical piano music. By using this transcription tool, users can transform live performance audio (or recordings) into editable, machine-readable MIDI — enabling tasks such as analysis, editing, remixing, or generation of piano music. ... -
7
TensorFlow Backend for ONNX
Tensorflow Backend for ONNX
Open Neural Network Exchange (ONNX) is an open standard format for representing machine learning models. ONNX is supported by a community of partners who have implemented it in many frameworks and tools. TensorFlow Backend for ONNX makes it possible to use ONNX models as input for TensorFlow. The ONNX model is first converted to a TensorFlow model and then delegated for execution on TensorFlow to produce the output. This is one of the two TensorFlow converter projects which serve different... -
8
YOLOv3
Object detection architectures and models pretrained on the COCO data
Fast, precise and easy to train, YOLOv5 has a long and successful history of real time object detection. Treat YOLOv5 as a university where you'll feed your model information for it to learn from and grow into one integrated tool. You can get started with less than 6 lines of code. with YOLOv5 and its Pytorch implementation. Have a go using our API by uploading your own image and watch as YOLOv5 identifies objects using our pretrained models. Start training your model without being an... -
9
Userge
Userge, Durable as a Serge
UserGe is a Powerful, Pluggable Telegram UserBot written in Python using Pyrogram by which you can Automate your Telegram account to work as you want. It comes with salient and descriptive features that help you to manage your task with some easy command. -
Total Network Visibility for Network Engineers and IT ManagersThis means every device on your network, and every interface on every device is automatically analyzed for performance, errors, QoS, and configuration.
-
10
Deep Daze
Simple command line tool for text to image generation
Simple command-line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network). In true deep learning fashion, more layers will yield better results. Default is at 16, but can be increased to 32 depending on your resources. Technique first devised and shared by Mario Klingemann, it allows you to prime the generator network with a starting image, before being steered towards the text. Simply specify the path to the image you wish to use, and... -
11
SexAI
A assistente virtual do sexo
-
12
Interactive Deep Colorization
Deep learning software for colorizing black and white images
Interactive Deep Colorization is a software project for colorizing black-and-white (grayscale) images using deep learning, allowing users to add a few hints (e.g. scribbles) and get a plausible, fully colorized output. The idea is to merge automatic colorization (via neural networks) with optional user guidance — so if the automatic model’s guess isn’t quite right, the user can nudge colors via hints to steer the result, achieving more controlled, satisfying outputs. The project includes... -
13
SageMaker Scikit-Learn Extension
A library of additional estimators and SageMaker tools based on scikit
...For unit tests, tox will use pytest to run the unit tests in a Python 3.7 interpreter. tox will also run flake8 and pylint for style checks. -
14
e-Dokyumento
e-Dokyumento is web-based Document Management System (DMS)
e-Dokyumento is opensource web-based Document Management System (DMS) A Document Management which automates the basic office document workflow such as receiving, filing, routing, and approving through capturing (scanning), digitizing (OCR Reading), storing, tagging, and electronically routing and approving (e-signature) of electronic documents. # Demo : https://e-dokyumento.herokuapp.com/ https://edokyu.seillig.com/ (refer to Readme.md for the... -
15
Machine Learning PyTorch Scikit-Learn
Code Repository for Machine Learning with PyTorch and Scikit-Learn
Initially, this project started as the 4th edition of Python Machine Learning. However, after putting so much passion and hard work into the changes and new topics, we thought it deserved a new title. So, what’s new? There are many contents and additions, including the switch from TensorFlow to PyTorch, new chapters on graph neural networks and transformers, a new section on gradient boosting, and many more that I will detail in a separate blog post. -
16
GANformer
Generative Adversarial Transformers
This is an implementation of the GANformer model, a novel and efficient type of transformer, explored for the task of image generation. The network employs a bipartite structure that enables long-range interactions across the image, while maintaining computation of linearly efficiency, that can readily scale to high-resolution synthesis. The model iteratively propagates information from a set of latent variables to the evolving visual features and vice versa, to support the refinement of... -
17
Voice Cloning App
A Python/Pytorch app for easily synthesising human voices
A Python/Pytorch app for easily synthesizing human voices. If you are using a language other than English you can add it to the app. Firstly, you'll need to find a deep speech model for your language by going to coqui. You'll then need to download the model.pbmm and alphabet.txt files for your language. Requires Windows 10 or Ubuntu 20.04+ operating system, 5GB+ Disk space, and NVIDIA GPU with at least 4GB of memory & driver version 456.38+ (optional). -
18
Acme
A library of reinforcement learning components and agents
Acme is a framework from DeepMind for building scalable and reproducible reinforcement learning agents. It emphasizes modular components, distributed training, and ease of experimentation. -
19
lightning library
Large-scale linear classification, regression and ranking in Python
lightning is a library for large-scale linear classification, regression and ranking in Python. -
20
Deep Feature Rotation Multimodal Image
Implementation of Deep Feature Rotation for Multimodal Image
Official implementation of paper Deep Feature Rotation for Multimodal Image Style Transfer [NICS'21] We propose a simple method for representing style features in many ways called Deep Feature Rotation (DFR), while still achieving effective stylization compared to more complex methods in style transfer. Our approach is a representative of the many ways of augmentation for intermediate feature embedding without consuming too much computational expense. Prepare your content image and style... -
21
DeepStack
The World's Leading Cross Platform AI Engine for Edge Devices
DeepStack is an AI API engine that serves pre-built models and custom models on multiple edge devices locally or on your private cloud. DeepStack runs completely offline and independent of the cloud. You can also install and run DeepStack on any cloud VM with docker installed to serve as your private, state-of-the-art and real-time AI server. -
22
Deep Learning Papers Reading Roadmap
Deep Learning papers reading roadmap for anyone who are eager to learn
Deep Learning Papers Reading Roadmap is a widely known curated reading plan for deep learning that helps newcomers and practitioners navigate the vast literature in a structured and intentional way. It is built around several guiding principles: moving from outline to detail, from older foundational papers to state-of-the-art work, and from generic to more specialized areas while keeping a focus on impactful contributions. The roadmap organizes papers into categories such as fundamentals,... -
23
Hugging Face Transformer
CPU/GPU inference server for Hugging Face transformer models
Optimize and deploy in production Hugging Face Transformer models in a single command line. At Lefebvre Dalloz we run in-production semantic search engines in the legal domain, in the non-marketing language it's a re-ranker, and we based ours on Transformer. In that setup, latency is key to providing a good user experience, and relevancy inference is done online for hundreds of snippets per user query. Most tutorials on Transformer deployment in production are built over Pytorch and FastAPI.... -
24
Google Research Football
Check out the new game server
Google Research Football is a reinforcement learning environment simulating soccer matches. It focuses on learning complex behaviors such as team collaboration and strategy formation in competitive settings. -
25
AWS Step Functions Data Science SDK
For building machine learning (ML) workflows and pipelines on AWS
The AWS Step Functions Data Science SDK is an open-source library that allows data scientists to easily create workflows that process and publish machine learning models using Amazon SageMaker and AWS Step Functions. You can create machine learning workflows in Python that orchestrate AWS infrastructure at scale, without having to provision and integrate the AWS services separately. The best way to quickly review how the AWS Step Functions Data Science SDK works is to review the related example notebooks. These notebooks provide code and descriptions for creating and running workflows in AWS Step Functions Using the AWS Step Functions Data Science SDK. ...
