Projects
- gradio — Python library for easily interacting with trained machine learning models
- gradio-awsbr-mmchatbot — This component enables multi-modal input for the Anthropic Claude v3 suite of models available from Amazon Bedrock
- gradio-bettertextbox — A better input text box for interacting with multi modal models
- gradio-blurhashimage — Python library for easily interacting with trained machine learning models
- gradio-box-promptable-image — A webcam-compatible Gradio input image component enabling prompting with bounding boxes.
- gradio-calendar — Gradio component for selecting dates with a calendar 📆
- gradio-clickable-arrow-dropdown — Dropdown component where clicking arrow on the side displays dropdown options
- gradio-client — Python library for easily interacting with trained machine learning models
- gradio-cofoldinginput — Component to enter protein and DNA sequences + small molecules for cofolding
- gradio-coolimage — Python library for easily interacting with trained machine learning models
- gradio-datepicker — Python library for easily interacting with trained machine learning models
- gradio-demotest — foo component
- gradio-devchatbot — Python library for easily interacting with trained machine learning models
- gradio-doctestaudio — Python library for easily interacting with trained machine learning models
- gradio-doctestcode — Python library for easily interacting with trained machine learning models
- gradio-doctestvideo — Python library for easily interacting with trained machine learning models
- gradio-editor3d — Bringing 3D design and editing capabilities to Gradio
- gradio-fabrie-textbox — fabrie_textbox
- gradio-folium — Display Interactive Maps Created with Folium
- gradio-foliumtest — Python library for easily interacting with trained machine learning models
- gradio-freddytb — Python library for easily interacting with trained machine learning models
- gradio-frp — Python library for easily interacting with trained machine learning models
- gradio-gptchatbot — Python library for easily interacting with trained machine learning models
- gradio-gradioworkbook — Workbook for interacting with models in AIConfig
- gradio-gradioworkbook-ap — Notebook for interacting with models in AIConfig
- gradio-grcalendar — Python library for easily interacting with trained machine learning models
- gradio-hdrimage — Component to load and display HDR images
- gradio-highlightedcode — A variant of the Code component that supports highlighting lines of code.
- gradio-highlightedtextbox — Editable Gradio textarea supporting highlighting
- gradio-highlightedtextlabeldefault — Modify the default label when selecting a word in the interactive HighlightedText component.
- gradio-huggingfacehub-search — Gradio component for searching Hugging Face Hub models, datasets, Spaces, and more
- gradio-iframe — Experimental empowered iFrame component based on existing HTML gradio component.
- gradio-image-annotation — A Gradio component that can be used to annotate images with bounding boxes.
- gradio-image-annotator — A component that allows you to annotate an image with points and boxes.
- gradio-image-prompter — A gradio component to upload images and process point/box prompts.
- gradio-imagefeed — A vertical feed of images which gets updated as a generater yields a new image.
- gradio-imageslider — A Gradio component for comparing two images. This component can be used in several ways: - as a **unified input / output** where users will upload a single image and an inference function will generate an image it can be compared to (see demo), - as a **manual upload input** allowing users to compare two of their own images (which can then be passed along elsewhere, e.g. to a model), - as **static output component** allowing users to compare two images generated by an inference function.
- gradio-leaderboard — Super fast , batteries included Leaderboard component ⚡️
- gradio-legacyimage — Python library for easily interacting with trained machine learning models
- gradio-log — A Log component for Gradio which can easily show some log file in the interface.
- gradio-mindbox — 成思维导图组件
- gradio-modal — A popup modal component
- gradio-model3dgs — Python library for easily interacting with trained machine learning models
- gradio-model4dgs — Python library for easily interacting with trained machine learning models
- gradio-molecule3d — Molecule3D custom component to visualize pdb or sdf files using 3Dmol.js
- gradio-molgallery2d — A Gradio component designed for displaying a gallery of 2D molecular structures.
- gradio-molgallery3d — A Gradio component designed for displaying an interactive gallery of 3D molecular structures.
- gradio-multimodalchatbot — Python library for easily interacting with trained machine learning models
- gradio-mycomponent3 — test
- gradio-mymodel3d — Python library for easily interacting with trained machine learning models
- gradio-notebook — Notebook for interacting with models in AIConfig
- gradio-offline — no summary
- gradio-orz — no summary
- gradio-pannellum — Python library for easily interacting with trained machine learning models
- gradio-paramviewer — A gradio component that renders a pretty table for python or javascript function or method parameters.
- gradio-pdf — Easily display PDFs in Gradio
- gradio-point-promptable-image — A webcam-compatible Gradio input component enabling point-based prompting.
- gradio-promptweighting — Simple component for creating prompt weighting for real-time generation.
- gradio-rich-textbox — Gradio custom component for rich text input
- gradio-sbmp-promptable-image — A webcam-compatible Gradio input image component enabling prompting with the most recently drawn bounding box and multiple points.
- gradio-stable-fork — no summary
- gradio-test-client-pypi — Python library for easily interacting with trained machine learning models
- gradio-test-pypi — Python library for easily interacting with trained machine learning models
- gradio-test2 — This is a test component
- gradio-test3 — This is a test component.
- gradio-testannimage — Python library for easily interacting with trained machine learning models
- gradio-testaudio — Test audio component
- gradio-testfallback — Python library for easily interacting with trained machine learning models
- gradio-testtextbox9 — Python library for easily interacting with trained machine learning models
- gradio-textwithattachments — Python library for easily interacting with trained machine learning models
- gradio-toggle — A custom component that toggles between on and off states. Ideal for intuitive user controls and dynamic input handling in machine learning models and data presentations.
- gradio-tools — Use Gradio Apps as tools for LLM Agents
- gradio-tunneling — no summary
- gradio-unifiedaudio — Python library for easily interacting with trained machine learning models
- gradio-url-buttons — Gradio custom compnent for adding URL buttons
- gradio-variableslider — Python library for easily interacting with trained machine learning models
- gradio-version-freeze — no summary
- gradio-videogallery — Python library for easily interacting with trained machine learning models
- gradio-yolov8-det — 基于 Gradio 的 YOLOv8 通用计算机视觉演示系统
- gradiologin — OAuth Login for Gradio
- gradioWrapper — A basic gradio class, class function, and functional decorator
- gradipy — A Lightweight Neural Network Library only using NumPy with Pytorch-like API
- GRADitude — A tool for the analysis of GRAD-seq data
- gradle-bodyguard — A tool that scans dependencies in your Gradle project and warns you about potential security issues
- gradle-profiler-pttest — Analyses the outcomes of two Gradle Profiler benchmarks with the Paired T-test statistical technique
- gradle-shizhan — Gradle 实战
- gradman — Baby Deep Learning Library
- gradnorm-pytorch — GradNorm - Pytorch
- gradools — gradools
- gradoptics — Differentiable Optics via Ray Tracing
- gradoptorch — Classical gradient based optimization in PyTorch
- gradpose — GradPose is a novel structural superimposition command-line tool and Python package for PDB files.
- gradpy — A package for automatic differentiation
- gradpyent — Create color gradients based on list-like input data
- gradsflow — An open-source AutoML Library based on PyTorch
- gradslam — gradSLAM: Dense SLAM meets Automatic Differentiation
- GradTree — A novel method for learning hard, axis-aligned decision trees with gradient descent.
- graduate-computer-graphics-nyu-csci-ga-2270-001 — Graduate Computer Graphics (NYU CSCI-GA.2270-001)
- graduate-pull — no summary
- gradysim — GrADyS-SIM NextGen is a framework for implementing distributed algorithms in a simulated network environment