Search Results for "batch" - Page 8
Sort By:
Showing 270 open source projects for "batch"
View related business solutions-
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.
-
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
-
1
Disco Diffusion
Notebooks, models and techniques for the generation of AI Art
...Initial QoL improvements added, including user-friendly UI, settings+prompt saving, and improved google drive folder organization. Now includes sizing options, intermediate saves and fixed image prompts and Perlin inits. the unexposed batch option since it doesn't work. -
2
RoBERTa for Chinese
RoBERTa Chinese pre-training model: RoBERTa for Chinese
...It provides TensorFlow and PyTorch-compatible model releases trained on large-scale Chinese text. The project follows the main RoBERTa training ideas, including removing next sentence prediction, using more diverse data, training longer, increasing batch size, and tuning optimization settings. Its training data includes news, community discussion, encyclopedia content, and other broad Chinese text sources. The repository also describes whole word masking for Chinese and provides examples for loading and fine-tuning models on sentence-pair matching tasks. Overall, it is a useful pretrained model resource for developers who want stronger Chinese BERT-style representations for classification, matching, reading comprehension, and related NLP tasks. -
3
Faster-Rcnn
This is a pytorch implementation library of faster-rcnn
...The project also includes learning rate scheduling through step and cosine methods, optimizer choices between Adam and SGD, adaptive learning rate behavior based on batch size, image cropping, FPS testing, video prediction, and batch prediction. It is a practical reference for users who want a more classical two-stage detector workflow in PyTorch. -
4
DeepLabv3 Plus
Encoder-Decoder with Atrous Separable Convolution
...The project also supports multi-GPU training, multiple backbones, learning rate schedules with step and cosine options, optimizer selection, and adaptive learning rate behavior based on batch size. It is useful for users who want a stronger semantic segmentation baseline than U-Net for scene-level segmentation tasks. -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
-
5
Cisco IOS Device Manager
Cisco IOS Device Management (backup, update image, save conf, reboot)
INFORMATION This program can be used for the following: - To collecting Cisco device information like: hostname, serial, model, IOS image, version, uptime, free memory (to CSV) - To enable the SCP service on the device (automaticly before file transfers) - To make a backup of the running-config and startup-config with SCP (with built-in MD5 hash comparison check) no TFTP/SFTP server needed. - To save the running-config to the startup-config (write memory) - To transfer a new image... -
6
AutoSub
A CLI script to generate subtitle files (SRT/VTT/TXT) for any video
...The tool supports multiple languages and can integrate with translation systems to produce subtitles in different languages. It is designed for automation, allowing batch processing of multiple media files. AutoSub leverages FFmpeg for media handling and integrates with speech recognition engines for transcription. It is particularly useful for content creators who want to quickly produce subtitles without manual effort. Overall, it simplifies the process of making media content accessible and searchable. -
7
A set of tools (command line and GUI) to provide a complete digital photo workflow for Unixes. EXIF headers are used as the central information repository, so users may change their software at any time without loosing any data.
-
8
MoCo v3
PyTorch implementation of MoCo v3
...MoCo v3 introduces improvements for training self-supervised ViTs by combining contrastive learning with transformer-based architectures, achieving strong linear and end-to-end fine-tuning performance on ImageNet benchmarks. The repository supports multi-node distributed training, automatic mixed precision, and linear scaling of learning rates for large-batch regimes. It also includes scripts for self-supervised pretraining, linear classification, and fine-tuning within the DeiT framework. -
9
Automation Orchestrator
Automation Orchestrator application to orchestrate digital processes
The Automation Orchestrator allows you to run a local Django Web Application to administrate and orchestrate automation scripts such as Nintex RPA botflows but you may also orchestrate other automation such as Python scripts, batch files, and other RPA tools. The Automation Orchestrator is tested with and supports Nintex RPA version = 15.1. As described on the official Django project site, it "is a high-level Python Web framework that encourages rapid development and clean, pragmatic design. Built by experienced developers, it takes care of much of the hassle of Web development, so you can focus on writing your app without needing to reinvent the wheel. ... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
10
Detectron2
Next-generation platform for object detection and segmentation
Detectron2 is Facebook AI Research's next generation software system that implements state-of-the-art object detection algorithms. It is a ground-up rewrite of the previous version, Detectron, and it originates from maskrcnn-benchmark. It is powered by the PyTorch deep learning framework. Includes more features such as panoptic segmentation, Densepose, Cascade R-CNN, rotated bounding boxes, PointRend, DeepLab, etc. Can be used as a library to support different projects on top of it. We'll... -
11
SimSiam
PyTorch implementation of SimSiam
SimSiam is a PyTorch implementation of “Exploring Simple Siamese Representation Learning” by Xinlei Chen and Kaiming He. The project introduces a minimalist approach to self-supervised learning that avoids negative pairs, momentum encoders, or large memory banks—key complexities of prior contrastive methods. SimSiam learns image representations by maximizing similarity between two augmented views of the same image through a Siamese neural network with a stop-gradient operation, preventing... -
12
Denoiser
Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)
...The implementation includes data augmentation techniques applied to the raw waveforms (e.g. noise mixing, reverberation) to improve model robustness and generalization to diverse noise types. The project supports both offline denoising (batch inference) and live audio processing (e.g. via loopback audio interfaces), making it practical for real-time use in calls or recording. The codebase includes training and evaluation scripts, configuration management via Hydra, and pretrained models on standard noise datasets. -
13
Savify
Download Spotify songs to mp3 with full metadata and cover art
...The tool integrates FFmpeg and yt-dlp to handle downloading, conversion, and formatting into common audio formats such as MP3. It enriches files with metadata including artist, album, cover art, and track information to maintain organized music libraries. savify supports batch downloading, enabling users to process entire playlists efficiently. It also provides configuration options for bitrate, file structure, and metadata sources. Overall, it offers a streamlined way to build offline music collections with structured metadata and automation. -
14
PyTorch SimCLR
PyTorch implementation of SimCLR: A Simple Framework
For quite some time now, we know about the benefits of transfer learning in Computer Vision (CV) applications. Nowadays, pre-trained Deep Convolution Neural Networks (DCNNs) are the first go-to pre-solutions to learn a new task. These large models are trained on huge supervised corpora, like the ImageNet. And most important, their features are known to adapt well to new problems. This is particularly interesting when annotated training data is scarce. In situations like this, we take the... -
15
Atgen A2 Automation
Atgen A2 is a radically simple Workload Automation & Scheduling tool.
Atgen A2 is a radically simple IT automation solution that automates application builds, continuous testing, data parsing & processing, report generation, batch processing, job scheduling, and many other IT needs. Avoid running repetitive batch jobs and managing access to deploy and update your applications — automate in a language that approaches plain English, using SSH or WinRM, with no agents to install on remote systems. https://www.atgensoft.com/ You can install a released version of Atgen A2 via package manager(yum) by downloading latest release. ... -
16
FixRes
Reproduces results of "Fixing the train-test resolution discrepancy"
...The approach is simple but highly effective, requiring no architectural modifications and working across diverse CNN backbones such as ResNet, ResNeXt, PNASNet, and EfficientNet. FixRes demonstrates that a mismatch between training and testing resolutions often leads to suboptimal accuracy, and fine-tuning the classifier and batch normalization layers at higher test resolutions significantly enhances performance. The repository includes pretrained models, feature embeddings, and evaluation scripts corresponding to the experiments reported in the NeurIPS 2019 paper “Fixing the train-test resolution discrepancy.” -
17
Nyaa.si Batch Uploader
Mass upload torrents to normal and sukebe versions of Nyaa.si
Note: I am NOT the coder for this software but the only client of the one who coded this in 2017 from a forum, and I have not heard back from him since. So regarding help on this I will do the best that I can... This software will let you upload torrents to nyaa.si and sukebe.nyaa.si in batch quantities instead of manually doing one by one. -
18
Nyaa.si Batch Torrent Upload
Batch torrent uploader for Nyaa.si
Batch upload via desktop to nyaa.si and sukebe.nyaa.si -
19
Super-résolution via CNN
Super resolution using a CNN, based on the work of the DGtal team
...This program will generate "model_epoch_ .pth" files corresponding to the model at epoch n, in a folder saved_model_u t_bs bs_tbs tbs_lr lr, where corresponds to the scale factor, bsthe size of the training batch, tbsthe size of the test batch and lrto the learning rate. Low res images should be located in a "dataset/input" folder, and high res targets in a "dataset/target" folder, where each different quality image has the same name in both folders. -
20
Albedo
A recommender system for discovering GitHub repos
Albedo is an open-source recommender system aimed at helping developers discover GitHub repositories by learning from activity signals. It treats repositories and developers as a graph of interactions and applies large-scale matrix factorization to model affinities, with Apache Spark providing the distributed data processing. The project focuses on implicit feedback—stars, watches, and other engagement metrics—so it can build useful recommendations without explicit ratings. A reproducible... -
21
Monkey-DL
Bulk download your favourite anime episodes from your favourite anime
...It integrates with tools like FFmpeg to handle post-processing tasks such as merging streams, converting formats, and optimizing output quality. The tool supports downloading single media files or entire playlists, enabling efficient batch operations. It includes options for selecting resolution, format, and output structure, giving users fine control over downloads. monkey-dl is built for simplicity, providing straightforward commands while still supporting advanced configurations. Its lightweight design makes it suitable for scripting and integration into automation workflows. ... -
22
MystiQ
Qt5/C++ FFmpeg Media Converter
...It allows users to perform operations such as transcoding, trimming, and format conversion without needing to use command-line tools. The application supports a wide range of codecs and formats, enabling compatibility across devices and platforms. It includes batch processing capabilities, allowing multiple files to be converted simultaneously. MystiQ also provides customizable encoding parameters, giving users control over quality and performance. Its interface is designed to be intuitive while still exposing advanced features for experienced users. Overall, it combines ease of use with powerful multimedia processing capabilities. -
23
BytePS
A high performance and generic framework for distributed DNN training
...In certain scenarios, BytePS can double the training speed compared with Horovod+NCCL. We show our experiment on BERT-large training, which is based on GluonNLP toolkit. The model uses mixed precision. We use Tesla V100 32GB GPUs and set batch size equal to 64 per GPU. Each machine has 8 V100 GPUs (32GB memory) with NVLink-enabled. Machines are inter-connected with 100 Gbps RDMA network. This is the same hardware setup you can get on AWS. -
24
Bangla TTS
Bangla text to speech synthesis in python
Bangla text to speech Multilingual (Bangla, English) real-time ([almost] in a GPU) speech synthesis library. Installation -------------------------------------- * Install Anaconda * conda create -n new_virtual_env python==3.6.8 * conda activate new_virtual_env * pip install -r requirements.txt * While running for the first time, keep your internet connection on to download the weights of the speech synthesis models (>500 MB) * For... -
25
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.