That’s called “Hugging Face’s Transformers” 🤗 (made via the reviewer dependency graph for Hugging Face’s Transformers)
Amid the whirlwind of AI advancements, Hugging Face has emerged as the backbone of innovation—much like how GitHub revolutionized code. It’s difficult to envision the current pace of AI development without Hugging Face’s contributions, especially its Transformers repository.
Let’s take a dive into the pace of development at Hugging Face’s Transformers repo by applying Dora Metrics using Middleware Open Source. We’ll cover three key aspects—no more, no less:
We’ll explore how Hugging Face’s fast-moving development is being held back by prolonged response times, extended rework cycles, and slow recovery, even after approvals are secured.
While Hugging Face powers through quick iterations, it finds itself "shackled" by delays in response time, rework, and post-approval wait times. The numbers tell the story: