Parvatham Siva Mallikarjun's picture

Parvatham Siva Mallikarjun

SivaMallikarjun
·

AI & ML interests

AI&ML intergrations

Recent Activity

updated a dataset about 18 hours ago
SivaMallikarjun/secure_retirement_dataset
published a dataset about 18 hours ago
SivaMallikarjun/secure_retirement_dataset
updated a dataset about 18 hours ago
SivaMallikarjun/world-languages-dataset
View all activity

Organizations

None yet

SivaMallikarjun's activity

reacted to abidlabs's post with 🤗👍 2 days ago
view post
Post
2931
JOURNEY TO 1 MILLION DEVELOPERS

5 years ago, we launched Gradio as a simple Python library to let researchers at Stanford easily demo computer vision models with a web interface.

Today, Gradio is used by >1 million developers each month to build and share AI web apps. This includes some of the most popular open-source projects of all time, like Automatic1111, Fooocus, Oobabooga’s Text WebUI, Dall-E Mini, and LLaMA-Factory.

How did we get here? How did Gradio keep growing in the very crowded field of open-source Python libraries? I get this question a lot from folks who are building their own open-source libraries. This post distills some of the lessons that I have learned over the past few years:

1. Invest in good primitives, not high-level abstractions
2. Embed virality directly into your library
3. Focus on a (growing) niche
4. Your only roadmap should be rapid iteration
5. Maximize ways users can consume your library's outputs

1. Invest in good primitives, not high-level abstractions

When we first launched Gradio, we offered only one high-level class (gr.Interface), which created a complete web app from a single Python function. We quickly realized that developers wanted to create other kinds of apps (e.g. multi-step workflows, chatbots, streaming applications), but as we started listing out the apps users wanted to build, we realized what we needed to do:

Read the rest here: https://x.com/abidlabs/status/1907886