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Showing 20 open source projects for "serv-u"
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Easily Host LLMs and Web Apps on Cloud RunRun frontend and backend services, batch jobs, host LLMs, and queue processing workloads without the need to manage infrastructure. Cloud Run gives you on-demand GPU access for hosting LLMs and running real-time AI—with 5-second cold starts and automatic scale-to-zero so you only pay for actual usage. New customers get $300 in free credit to start.
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Build AI Apps with Gemini 3 on Vertex AIVertex AI gives developers access to Gemini 3—Google’s most advanced reasoning and coding model—plus 200+ foundation models including Claude, Llama, and Gemma. Build generative AI apps with Vertex AI Studio, customize with fine-tuning, and deploy to production with enterprise-grade MLOps. New customers get $300 in free credits.
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x-unet
Implementation of a U-net complete with efficient attention
Implementation of a U-net complete with efficient attention as well as the latest research findings. For 3d (video or CT / MRI scans). -
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Video Diffusion - Pytorch
Implementation of Video Diffusion Models
Implementation of Video Diffusion Models, Jonathan Ho's new paper extending DDPMs to Video Generation - in Pytorch. Implementation of Video Diffusion Models, Jonathan Ho's new paper extending DDPMs to Video Generation - in Pytorch. It uses a special space-time factored U-net, extending generation from 2D images to 3D videos. 14k for difficult moving mnist (converging much faster and better than NUWA) - wip. Any new developments for text-to-video synthesis will be centralized at Imagen-pytorch. For conditioning on text, they derived text embeddings by first passing the tokenized text through BERT-large. ... -
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Imagen - Pytorch
Implementation of Imagen, Google's Text-to-Image Neural Network
Implementation of Imagen, Google's Text-to-Image Neural Network that beats DALL-E2, in Pytorch. It is the new SOTA for text-to-image synthesis. Architecturally, it is actually much simpler than DALL-E2. It consists of a cascading DDPM conditioned on text embeddings from a large pre-trained T5 model (attention network). It also contains dynamic clipping for improved classifier-free guidance, noise level conditioning, and a memory-efficient unit design. It appears neither CLIP nor prior... -
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Pytorch-toolbelt
PyTorch extensions for fast R&D prototyping and Kaggle farming
A pytorch-toolbelt is a Python library with a set of bells and whistles for PyTorch for fast R&D prototyping and Kaggle farming. Easy model building using flexible encoder-decoder architecture. Modules: CoordConv, SCSE, Hypercolumn, Depthwise separable convolution and more. GPU-friendly test-time augmentation TTA for segmentation and classification. GPU-friendly inference on huge (5000x5000) images. Every-day common routines (fix/restore random seed, filesystem utils, metrics). Losses:... -
Cut Cloud Costs with Google Compute EngineSave on compute costs with Compute Engine. Reduce your batch jobs and workload bill 60-91% with Spot VMs. Compute Engine's committed use offers customers up to 70% savings through sustained use discounts. Plus, you get one free e2-micro VM monthly and $300 credit to start.
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LatentSync
Taming Stable Diffusion for Lip Sync
...In effect, given a source video (with masked or reference frames) and an audio track, LatentSync directly generates frames whose lip motions and expressions align with the audio, producing convincing talking-head or animated lip-sync output. The system leverages a U-Net diffusion backbone, with cross-attention of audio embeddings (via an audio encoder) and reference video frames to guide generation, and applies a set of loss functions (temporal, perceptual, sync-net based) to enforce lip-sync accuracy, visual fidelity, and temporal consistency. Over versions, LatentSync has improved temporal stability and lowered resource requirements — making inference more practical (e.g. 8 GB VRAM for earlier versions, somewhat higher for latest models). -
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Discord Token & Message Spammer
best open source discord spammer (token-webhook&more)
easy to use, set the tokens & channels and have fun, don't use it in a bad way if you catch my drift, if you want to use it you better use a vpn so discord won't ban you're ip smh. DMS version 0.5 the installer file is safe but if u dont trust it just go to the github page and download the source files from there https://github.com/SStorm20/Discord-Message-Spammer-DSM ill keep updating this tool for sure tags: discord token spammer, discord raid tool, discord , discord tool discord tokens, chat spammer license By downloading this, you agree to the Commons Clause license and that you're not allowed to sell this repository or any code from this repository. ... -
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Demucs
Code for the paper Hybrid Spectrogram and Waveform Source Separation
Demucs (Deep Extractor for Music Sources) is a deep-learning framework for music source separation—extracting individual instrument or vocal tracks from a mixed audio file. The system is based on a U-Net-like convolutional architecture combined with recurrent and transformer elements to capture both short-term and long-term temporal structure. It processes raw waveforms directly rather than spectrograms, allowing for higher-quality reconstruction and fewer artifacts in separated tracks. The repository includes pretrained models for common tasks such as isolating vocals, drums, bass, and accompaniment from stereo music, achieving state-of-the-art results in benchmarks like MUSDB18. ... -
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fastMRI
A large open dataset + tools to speed up MRI scans using ML
...The repository provides an open-source PyTorch framework with data loaders, subsampling utilities, reconstruction models, and evaluation metrics, supporting both research reproducibility and practical experimentation. It includes reference implementations for key MRI reconstruction architectures such as U-Net and Variational Networks (VarNet), along with example scripts for model training and evaluation using the PyTorch Lightning framework. The project also releases several fully anonymized public MRI datasets, including knee, brain, and prostate scans. -
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audio-diffusion-pytorch
Audio generation using diffusion models, in PyTorch
...Includes models for unconditional audio generation, text-conditional audio generation, diffusion autoencoding, upsampling, and vocoding. The provided models are waveform-based, however, the U-Net (built using a-unet), DiffusionModel, diffusion method, and diffusion samplers are both generic to any dimension and highly customizable to work on other formats. Note: no pre-trained models are provided here, this library is meant for research purposes. -
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CPT
CPT: A Pre-Trained Unbalanced Transformer
A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and Generation. We replace the old BERT vocabulary with a larger one of size 51271 built from the training data, in which we 1) add missing 6800+ Chinese characters (most of them are traditional Chinese characters); 2) remove redundant tokens (e.g. Chinese character tokens with ## prefix); 3) add some English tokens to reduce OOV. Position Embeddings We extend the max_position_embeddings from 512 to 1024. We... -
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Yellowbrick
Visual analysis and diagnostic tools to facilitate ML selection
Yellowbrick extends the Scikit-Learn API to make model selection and hyperparameter tuning easier. Under the hood, it’s using Matplotlib. Yellowbrick is a suite of visual diagnostic tools called "Visualizers" that extend the scikit-learn API to allow human steering of the model selection process. In a nutshell, Yellowbrick combines scikit-learn with matplotlib in the best tradition of the scikit-learn documentation, but to produce visualizations for your machine learning workflow. -
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StudioGAN
StudioGAN is a Pytorch library providing implementations of networks
...Moreover, StudioGAN provides an unprecedented-scale benchmark for generative models. The benchmark includes results from GANs (BigGAN-Deep, StyleGAN-XL), auto-regressive models (MaskGIT, RQ-Transformer), and Diffusion models (LSGM++, CLD-SGM, ADM-G-U). StudioGAN is a self-contained library that provides 7 GAN architectures, 9 conditioning methods, 4 adversarial losses, 13 regularization modules, 6 augmentation modules, 8 evaluation metrics, and 5 evaluation backbones. Among these configurations, we formulate 30 GANs as representatives. Each modularized option is managed through a configuration system that works through a YAML file. -
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U-Net Fusion RFI
U-Net for RFI Detection based on @jakeret's implementation
...This project will use the aoflagger program within the code, so you may need to ensure that any environment variables are set for aoflagger before use. cite: https://sourceforge.net/p/u-net-fusion-rfi/wiki/cite/ -
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NiftyNet
An open-source convolutional neural networks platform for research
An open-source convolutional neural networks platform for medical image analysis and image-guided therapy. NiftyNet is a TensorFlow-based open-source convolutional neural networks (CNNs) platform for research in medical image analysis and image-guided therapy. NiftyNet’s modular structure is designed for sharing networks and pre-trained models. Using this modular structure you can get started with established pre-trained networks using built-in tools. Adapt existing networks to your imaging... -
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Linux for Beagleboard-xm
A Tailored Small Linux for Beagleboard-xm
Beagleboard-xm is a powerful chip with a cortex-A8 CPU and a DSP. I have the plan to build an OCR gadget using it with Linux. As a by product I will post my tailored Linux kernel and u-boot, and all relevant stuff here, from now on. I was shocked by the blocking of Chinese citizens from accessing some of the contents on sourceforge. I deeply regret the outrageous action initiated, even though I fully understand the reasoning behind it. -
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Dutch sentiment analysis engine
Een module om de sentiment van een stuk Nederlandse tekst to bepalen
...Deze applicatie is ontwikkeld door Incentro om te voldoen aan klantaanvragen voor een sentimentanalyse module voor de Nederlandse taal. Momenteel is de module in alpha versie beschikbaar en een beta versie wordt verwacht in november 2012. Als u ons wilt helpen bij het ontwikkelen of testen van deze module, neem dan contact op met Incentro via +31[0]15 76 40 750 - of info {at} incentro.com. -
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'Text to Voice' or 'Text to Speech' is 1 of the coolest Firefox add-ons. It gives ur brwsr the pwr of speech. Select txt, clck the bttn on the bttm rite & this add-on spks the selectd txt 4 u. Isn't it brllant? Moreovr odio file cn b dnloaded as
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Low Cost Intel, Software Embedded! By integrate SBC ‘Gumstix’ with Real-time sensors! IMU(heading, roll), GPS, Pressure, Airspeed, Sonar. Apply Kalman Filtering -> ADC’s -> PXA255 ‘Linux – U boot’; “Glass Cockpit Open source” + 2.4G/ WiFi
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3A-TRE
3A-TRE evaluates traditionally logical expressions under 3 assumptions
...In this case, the dependent test modules are always assumed to be true when their results are not available. We call this a stub assumption (SA). 3A-TRE example: echo "CWA: (T and U)" | java -jar PTRE.jar Result: F 3A-PTRE example: (P means possible results) echo "OWA: (T,U and U,F)" | java -jar PTRE.jar Result: U,F -
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manualxml
Manual XML parsin
...However my emp***er decided that it would be cool and fun if I manually sat and generated/parsed xml. First it was bad but now i totally get it... THIS IS AWESOME... So i decided why not do this for the whole world. ALl u have to do is 1. Email me XML and wait 2. In about a week I will parse the xml and email back simple :) SPECIAL FEATURE: NATURAL LANGUAGE PROCESSING make spelling mistakes and I will get it :) Pls comment below, I love this s***
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