Search Results for "pass"
Sort By:
Showing 121 open source projects for "pass"
View related business solutions-
$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.
-
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
-
1
LiteLLM
lightweight package to simplify LLM API calls
Call all LLM APIs using the OpenAI format [Anthropic, Huggingface, Cohere, Azure OpenAI etc.] liteLLM supports streaming the model response back, pass stream=True to get a streaming iterator in response. Streaming is supported for OpenAI, Azure, Anthropic, and Huggingface models. -
2
Fast3R
Fast3R: Towards 3D Reconstruction of 1000+ Images in One Forward Pass
Fast3R is Meta AI’s official CVPR 2025 release for “Towards 3D Reconstruction of 1000+ Images in One Forward Pass.” It represents a next-generation feedforward 3D reconstruction model capable of producing dense point clouds and camera poses for hundreds to thousands of images or video frames in a single inference pass—eliminating the need for slow, iterative structure-from-motion pipelines. Built on PyTorch Lightning and extending concepts from DUSt3R and Spann3r, Fast3R unifies multi-view geometry, depth estimation, and camera registration within a single transformer-based architecture. ... -
3
Transformer Debugger
Tool for exploring and debugging transformer model behaviors
...It combines automated interpretability methods with sparse autoencoders, enabling researchers to analyze how specific neurons, attention heads, and latent features contribute to a model’s outputs. TDB allows users to intervene directly in the forward pass of a model and observe how such interventions change predictions, making it possible to answer questions like why a token was selected or why an attention head focused on a certain input. It automatically identifies and explains the most influential components, highlights activation patterns, and maps relationships across circuits within the model. ... -
4
No AI slop
Removes 20+ patterns of AI slop from any piece of writing
...It can also analyze a passage for these patterns without claiming to determine whether AI created it. When editing, it makes the minimum effective changes and returns the revised draft with a brief explanation. A built-in evaluation file provides pass-or-fail checks that the skill applies to its own work. The project can be installed in Claude Code, Codex, other AI harnesses, and packaged ChatGPT or Codex plugin environments. -
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.
-
5
OpenAI Privacy Filter
Bidirectional token-classification model for identifiable info
OpenAI Privacy Filter is an open-weight machine learning model designed to detect and mask personally identifiable information in text with high efficiency and contextual awareness. It operates as a bidirectional token classification system that labels sensitive data in a single forward pass rather than generating text sequentially, enabling fast processing for large datasets. The model supports long-context inputs, allowing it to analyze extensive documents without chunking, which improves consistency in redaction tasks. It can run locally on standard hardware, ensuring that sensitive information never leaves the user’s environment and supporting privacy-first workflows. ... -
6
tqdm
A Fast, Extensible Progress Bar for Python and CLI
...Simply wrap any iterable with tqdm(iterable), and sit back and watch that progress meter go! tqdm can be wrapped around any iterable, or executed as a module with pipes. Just by inserting tqdm (or python -m tqdm) between pipes will pass through all stdin to stdout while printing progress to stderr. tqdm does not require any dependencies, has a very low overhead and uses smart algorithms to predict the remaining time and skip unnecessary iteration displays. It works on just about any platform, console or in a GUI, as well as IPython/Jupyter notebooks. -
7
FlashAttention
Fast and memory-efficient exact attention
...The project provides implementations of FlashAttention, FlashAttention-2, and newer iterations optimized for modern GPU architectures such as NVIDIA Hopper and AMD accelerators. By improving both forward and backward pass efficiency, it enables training and inference of large language models with longer sequence lengths and higher throughput. The library integrates with PyTorch and supports various attention configurations, including causal masking, multi-query attention, and rotary embeddings. -
8
LangExtract
A Python library for extracting structured information
...LangExtract supports a wide range of models, including Google Gemini, OpenAI GPT, and local LLMs via Ollama, making it adaptable to different deployment environments and compliance needs. The system excels at handling long documents using optimized chunking, multi-pass extraction, and parallel processing to ensure both high recall and structured consistency. -
9
PML
The easiest way to use deep metric learning in your application
This library contains 9 modules, each of which can be used independently within your existing codebase, or combined together for a complete train/test workflow. To compute the loss in your training loop, pass in the embeddings computed by your model, and the corresponding labels. The embeddings should have size (N, embedding_size), and the labels should have size (N), where N is the batch size. The TripletMarginLoss computes all possible triplets within the batch, based on the labels you pass into it. Anchor-positive pairs are formed by embeddings that share the same label, and anchor-negative pairs are formed by embeddings that have different labels. ... -
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.
-
10
Codex gpt-5.6 Instruct
A Codex CLI jailbreak prompt and test pack for gpt-5.6-sol
...A Python deployment utility can preview changes, install a selected configuration, create backups, and restore earlier settings. The repository includes bilingual prompt banks, recorded model outputs, pass-or-fail results, historical reports, and candidate comparisons. Its evaluation workflow organizes scenarios by language, length, and task family. The project is intended for adversarial prompt testing rather than ordinary application development. -
11
sqlmap
Automatic SQL injection and database takeover tool
sqlmap is a powerful, feature-filled, open source penetration testing tool. It makes detecting and exploiting SQL injection flaws and taking over the database servers an automated process. sqlmap comes with a great range of features that along with its powerful detection engine make it the ultimate penetration tester. It offers full support for MySQL, Oracle, PostgreSQL, Microsoft SQL Server, Microsoft Access, IBM DB2, SQLite, Firebird, and many other database management systems. It also... -
12
Microsoft Azure CLI
Azure command-line interface
A great cloud needs great tools; we're excited to introduce Azure CLI, our next-generation multi-platform command-line experience for Azure. Take a test run now from Azure Cloud Shell! We support tab completion for groups, commands, and some parameters. You can use the --query parameter and the JMESPath query syntax to customize your output. With the Azure CLI Tools Visual Studio Code extension, you can create .azcli files and use these features. IntelliSense for commands and their... -
13
Dia
A TTS model capable of generating ultra-realistic dialogue
Dia is a neural text-to-speech model designed specifically for generating ultra-realistic dialogue in a single pass. Instead of focusing on isolated sentences or flat narration, it is optimized for conversational audio, complete with natural turn-taking, prosody, and pacing. The model can be conditioned on a reference audio sample, allowing you to control emotion, tone, and other stylistic aspects of the speech. It can also produce nonverbal vocalizations like laughter, coughs, clearing the throat, and similar sounds, which are crucial for making synthetic conversations feel human. ... -
14
img2dataset
Easily turn large sets of image urls to an image dataset
...Can download, resize and package 100M urls in 20h on one machine. Also supports saving captions for url+caption datasets. Opt-out directives: Websites can pass the http headers X-Robots-Tag: noai, X-Robots-Tag: noindex , X-Robots-Tag: noimageai and X-Robots-Tag: noimageindex By default img2dataset will ignore images with such headers. -
15
LocalGPT
Chat with your documents on your local device using GPT models
...The retrieval system combines semantic similarity, keyword matching, late chunking, contextual enrichment, and sentence-level pruning. A smart router chooses between retrieval-augmented generation and direct model responses for each query. An independent verification pass is intended to improve answer reliability before results are returned. The platform works with Ollama models, offers a browser interface and API, and can run through local or Docker-based setups. It supports CPU and several hardware acceleration environments while retaining conversation history within a session. -
16
GraalPy
A Python 3 implementation built on GraalVM
GraalPy is a high-performance implementation of the Python language for the JVM built on GraalVM. GraalPy is a Python 3.11 compliant runtime. It has first-class support for embedding in Java and can turn Python applications into fast, standalone binaries. GraalPy is ready for production running pure Python code and has experimental support for many popular native extension modules. -
17
VOID
Video Object and Interaction Deletion
VOID is an advanced AI video processing system developed by Netflix that focuses on removing objects from videos while preserving the physical and visual realism of the surrounding environment. Unlike traditional inpainting methods that only erase pixels or simple artifacts, VOID models the full interaction dynamics between objects and their environment, including shadows, reflections, and even physical consequences such as movement or balance changes. Built on top of transformer-based... -
18
folium
Python data, Leaflet.js maps
...The library has a number of built-in tilesets from OpenStreetMap, Mapbox, and Stamen, and supports custom tilesets with Mapbox or Cloudmade API keys. folium supports both Image, Video, GeoJSON and TopoJSON overlays. To create a base map, simply pass your starting coordinates to Folium. To display it in a Jupyter notebook, simply ask for the object representation. The default tiles are set to OpenStreetMap, but Stamen Terrain, Stamen Toner, Mapbox Bright, and Mapbox Control Room, and many others tiles are built in. -
19
HunyuanOCR
OCR expert VLM powered by Hunyuan's native multimodal architecture
HunyuanOCR is an open-source, end-to-end OCR (optical character recognition) Vision-Language Model (VLM) developed by Tencent‑Hunyuan. It’s designed to unify the entire OCR pipeline, detection, recognition, layout parsing, information extraction, translation, and even subtitle or structured output generation, into a single model inference instead of a cascade of separate tools. Despite being fairly lightweight (about 1 billion parameters), it delivers state-of-the-art performance across a... -
20
dstack
Open-source tool designed to enhance the efficiency of workloads
dstack is an open-source tool designed to enhance the efficiency of running ML workloads in any cloud (AWS, GCP, Azure, Lambda, etc). It streamlines development and deployment, reduces cloud costs, and frees users from vendor lock-in. -
21
Flask-WTF
Simple integration of Flask and WTForms, including CSRF
Simple integration of Flask and WTForms, including CSRF, file upload, and reCAPTCHA. Integration with WTForms. Secure Form with CSRF token. Global CSRF protection. reCAPTCHA support. File upload that works with Flask-Uploads. Internationalization using Flask-Babel. -
22
Denoising Diffusion Probabilistic Model
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
...It uses denoising score matching to estimate the gradient of the data distribution, followed by Langevin sampling to sample from the true distribution. If you simply want to pass in a folder name and the desired image dimensions, you can use the Trainer class to easily train a model. -
23
npcpy
The AI toolkit for the AI developer
...Welcome to npcpy, the core library of the NPC Toolkit that supercharges natural language processing pipelines and agent tooling. npcpy is a flexible framework for building state-of-the-art applications and conducting novel research with LLMs. The structure of npcpy also allows one to pass an npc to get_llm_response in addition to using the NPC's wrapped method, allowing you to be flexible in your implementation and testing. -
24
ML Sharp
Sharp Monocular View Synthesis in Less Than a Second
ML Sharp is a research code release that turns a single 2D photograph into a photorealistic 3D representation that can be rendered from nearby viewpoints. Instead of requiring multi-view input, it predicts the parameters of a 3D Gaussian scene representation directly from one image using a single forward pass through a neural network. The core idea is speed: the 3D representation is produced in under a second on a standard GPU, and then the resulting scene can be rendered in real time to generate new views interactively. The representation is metric, meaning it supports camera movements with an absolute scale rather than only relative depth cues, which is useful for consistent viewpoint changes and downstream spatial tasks. ... -
25
Dream Textures
Stable Diffusion built-in to Blender
...Use the 'Seamless' option to create textures that tile perfectly with no visible seam. Texture entire scenes with 'Project Dream Texture' and depth to image. Re-style animations with the Cycles render pass. Run the models on your machine to iterate without slowdowns from a service. Create textures, concept art, and more with text prompts. Learn how to use the various configuration options to get exactly what you're looking for. Texture entire models and scenes with depth to image. Inpaint to fix up images and convert existing textures into seamless ones automatically. ...
