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Gradio

Appears in 11 awesome lists

Build and share delightful machine learning apps, all in Python. The de facto standard for creating interactive ML demos with automatic UI generation from function signatures. Powers thousands of Hugging Face Spaces.

Open github.comgradio-app/gradio

Found in these lists

Awesome Data Analysis

Section: Tools · Tool for creating and sharing machine learning applications.

FreshScore 80

AWESOME DATA SCIENCE

Section: Miscellaneous Tools · Create customizable UI components around machine learning models

FreshScore 92

Awesome Machine Learning

Section: Python · A Python library for quickly creating and sharing demos of models. Debug models interactively in your browser, get feedback from collaborators, and generate public links without deploying anything.

FreshScore 93

Awesome MLOps

Section: Model Serving · Create customizable UI components around your models.

FreshScore 80

Awesome Open Source AI

Section: 1. Core Frameworks & Libraries · Build and share delightful machine learning apps, all in Python. The de facto standard for creating interactive ML demos with automatic UI generation from function signatures. Powers thousands of Hugging Face Spaces.

FreshScore 89

Awesome Production Machine Learning

Section: Industry Strength Visualisation · Quickly create and share demos of models - by only writing Python. Debug models interactively in your browser, get feedback from collaborators, and generate public links without deploying anything.

FreshScore 92

Awesome Python

Section: Data Visualization · Build and share machine learning apps, all in Python.

FreshScore 94

Awesome Python Data Science

Section: Deployment · Create UIs for your machine learning model in Python in 3 minutes.

ActiveScore 71

Awesome Data Science with Python

Section: General · Create UIs for your machine learning model.

FreshScore 82

awesome-python

Section: Data Science and Analytics · Build and share delightful machine learning apps, all in Python. Star to support our work!

FreshScore 81

Awesome Systematic Trading

Section: Visualization · | Python | - Build and share delightful machine learning apps, all in Python.

FreshScore 89

TensorFlow

How to use the Hexagon Delegate to speed up model inference on mobile and edge devices. Also see blog post Accelerating TensorFlow Lite on Qualcomm Hexagon DSPs.

In 23 listsDetails

PyTorch

(label: good first issue) PyTorch is an open source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing.

In 16 listsDetails

Opik

Comet's open-source AI observability and evaluation platform: deep tracing of LLM calls, conversation logging, and agent activity, plus built-in eval metrics, prompt versioning, guardrails, and the Opik Agent Optimizer. Worth including because it unifies observability, verification, and…

In 16 listsDetails

transformers

(formerly known as pytorch-transformers and pytorch-pretrained-bert) provides state-of-the-art general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet, CTRL...) for Natural Language Understanding (NLU) and Natural Language Generation (NLG) with over 32+ pretrained models in…

In 14 listsDetails

Colossal-AI

(from Hpcaitech) - A Unified Deep Learning System for Large-Scale Parallel Training (1D, 2D, 2.5D, 3D and sequence parallelism, and ZeRO protocol).

In 14 listsDetails

Apache Airflow

"Use airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command line utilities make performing complex surgeries on DAGs a snap. The rich user interface makes it…

In 13 listsDetails

Ray

A fast and simple framework for building and running distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library. ray.io

In 13 listsDetails

Haystack

Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search,…

In 13 listsDetails