Search Results for "issues" - Page 3
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Showing 65 open source projects for "issues"
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CogView
Text-to-Image generation. The repo for NeurIPS 2021 paper
...With 4 billion parameters, it was one of the earliest transformer-based models to successfully generate high-quality images from natural language descriptions in Chinese, with partial support for English via translation. The model incorporates innovations such as PB-relax and Sandwich-LN to enable stable training of very deep transformers without NaN loss issues. CogView supports multiple tasks beyond text-to-image, including image captioning, post-selection (ranking candidate images by relevance to a prompt), and super-resolution (upscaling model-generated images). The repository provides pretrained models, inference scripts, and training examples, along with a Docker environment for reproducibility. -
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Sweep AI
Sweep: AI-powered Junior Developer for small features and bug fixes
Let Sweep handle your tech debt so you can focus on the exciting problems. Sweep is an AI junior developer that transforms bug reports & feature requests into code changes. Describe bugs, small features, and refactors like you would to a junior developer and Sweep. -
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VAMS
Virtual Assistant Maintenance System
Virtual Assistant Maintenance System also knowns as VAMS is an AI software application, that helps users with some computer maintenance issues. Application Requirements: Operating System: Windows 8.1/10 /11 Processor: Intel Core i5 or equivalent RAM: 4GB or higher Free Disk Space: 500MB -
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Img2Txt
Img2Txt - Extract Text From Images using AI
...The application features a simple and modern user-friendly interface created using customtkinter, allowing users to easily process images and obtain the text within them. Support me at : https://www.buymeacoffee.com/zsynctic it will motivate me and it will make me create more projects Support For any questions or issues, please open an issue on the Img2Txt GitHub repository. Warning: When running Img2Txt.exe a Blue Window Might Popup. To Run The Application You Have To Press More Info And Then Run Anyways. © zSynctic -
Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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TensorFlow Backend for ONNX
Tensorflow Backend for ONNX
...This is one of the two TensorFlow converter projects which serve different purposes in the ONNX community. ONNX-TF requires ONNX (Open Neural Network Exchange) as an external dependency, for any issues related to ONNX installation, we refer our users to ONNX project repository for documentation and help. Notably, please ensure that protoc is available if you plan to install ONNX via pip. -
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Grade School Math
8.5K high quality grade school math problems
...The repository maintains strict formatting (e.g. JSONL) for problem + answer pairs, and is used broadly in research to benchmark model performance under “word problem” settings. Issues are tracked (people report incorrect problems, ambiguous statements), and contributions are possible for cleaning or expanding the set. -
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Paperless-ng
A supercharged version of paperless, scan, index and archive docs
Paperless is a simple Django application running in two parts, a Consumer (the thing that does the indexing) and a Web server (the part that lets you search & download already-indexed documents). Paper is a nightmare. Environmental issues aside, there’s no excuse for it in the 21st century. It takes up space, collects dust, doesn’t support any form of a search feature, indexing is tedious, it’s heavy and prone to damage & loss. I wrote this to make “going paperless” easier. I do not have to worry about finding stuff again. I feed documents right from the post box into the scanner and then shred them. ... -
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CleverHans
An adversarial example library for constructing attacks
...The CleverHans library is under continual development, always welcoming contributions of the latest attacks and defenses. In particular, we always welcome help with resolving the issues currently open. Since v4.0.0, CleverHans supports 3 frameworks: JAX, PyTorch, and TF2. We are currently prioritizing implementing attacks in PyTorch, but we very much welcome contributions for all 3 frameworks. In versions v3.1.0 and prior, CleverHans supported TF1; the code for v3.1.0 can be found under cleverhans_v3.1.0/ or by checking out a prior Github release. ... -
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Transformer TTS
Implementation of a Transformer based neural network
...The system separates alignment learning and acoustic modeling: an autoregressive Transformer is used as an aligner to extract phoneme-to-frame durations, while a non-autoregressive “ForwardTransformer” generates mel-spectrograms conditioned on text and durations. This design addresses common autoregressive issues such as repetition, skipped words, and unstable attention, and results in robust, fast synthesis where all frames are predicted in parallel. The repository ships with tooling to build datasets (especially LJSpeech) and create training data, plus scripts to train both the aligner and the TTS model, monitor training with TensorBoard, and resume or reset training runs. -
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.
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10
CC-Net
Tools to download and cleanup Common Crawl data
...The repository documents practical concerns like HTTP failures, snapshot differences, and stats JSONs, reflecting community use across many languages. While powerful, the repo has been archived and is read-only, so users should expect to run it as-is or fork for maintenance. Even in archived state, issues and releases pages remain useful references for implementation details and dataset lineage. -
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Reliable Metrics for Generative Models
Code base for the precision, recall, density, and coverage metrics
...For example, they fail to detect the match between two identical distributions, they are not robust against outliers, and the evaluation hyperparameters are selected arbitrarily. We propose density and coverage metrics that solve the above issues. -
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LabelImg
Graphical image annotation tool and label object bounding boxes
...Linux/Ubuntu/Mac requires at least Python 2.6 and has been tested with PyQt 4.8. However, Python 3 or above and PyQt5 are strongly recommended. Virtualenv can avoid a lot of the QT / Python version issues. Build and launch using the instructions. Click 'Change default saved annotation folder' in Menu/File. Click 'Open Dir'. Click 'Create RectBox'. Click and release left mouse to select a region to annotate the rect box. You can use right mouse to drag the rect box to copy or move it. The annotation will be saved to the folder you specify. ... -
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Improved GAN
Code for the paper "Improved Techniques for Training GANs"
...It provides implementations of experiments conducted on datasets such as MNIST, SVHN, CIFAR-10, and ImageNet. The project focuses on demonstrating enhanced training methods for Generative Adversarial Networks, addressing stability and performance issues that were common in earlier GAN models. The repository includes training scripts, evaluation methods, and pretrained configurations for reproducing experimental results. By offering structured experiments across multiple datasets, it allows researchers to study and replicate the improvements described in the paper. Although the project is archived and not actively maintained, it remains a reference point in the history of GAN research, influencing subsequent model training approaches. -
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The Deep Review
A collaboratively written review paper on deep learning, genomics, etc
...The project operates on an open contribution model, welcoming contributions from anyone. To see what's incoming, check the open pull requests. For project discussion and planning see the Issues. As of writing, we are aiming to publish an update of the deep review. We will continue to make project preprints available on bioRxiv or another preprint service and aim to continue publishing the finished reviews in a peer-reviewed venue as well. Like the initial release, we are planning for an open and collaborative effort. New contributors are welcome and will be listed as version 2.0 authors. ... -
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llmverify-npm
You need a safety layer between your LLM and your users.
...Local-first verification, safety monitoring, and guardrails for any LLM 100% Local | No Telemetry | Privacy-First | 500 free calls/day Links Product Page: subodhkc.com/products/llmverify npm: npmjs.com/package/llmverify GitHub: github.com/subodhkc/llmverify-npm Python Package (PyPI): github.com/subodhkc/llmverify Author: Subodh KC — AI governance, compliance, and security leader Feature One-liner What it catches Verify output await verify(aiResponse) Hallucinations, harmful content, quality issues Block injections isInputSafe(userMessage) Prompt injection, jailbreaks, malicious input Redact PII redactPII(text) Emails, phones, SSNs, credit cards, API keys Fix broken JSON repairJSON(broken) Missing brackets, trailing commas, unquoted keys Monitor health monitorLLM(client) Latency spikes, token drift, behavioral changes Sentinel tests sentinel.quick(client, model) LLM regressions b
