What I Learned Quantizing DistilBERT to ONNX for Browser Inference
This story is from 2026-09-18. It is preserved in the archive; the latest stories are on the live feed.
What I Learned Quantizing DistilBERT to ONNX for Browser Inference I built a support-ticket classifier — 77 banking intents, fine-tuned DistilBERT, Banking77 — and got it to 92.2% accuracy. Then I tried to ship it, and ran into the actual problem: the checkpoint was 256 MB and took ~9 ms per query…
Read the full story at DEV Community — Machine Learning ↗
Timeline · 1 report
- 2026-09-18 03:20 · DEV Community — Machine Learning
What I Learned Quantizing DistilBERT to ONNX for Browser Inference
More stories
- Gemini Hacked Three Companies in First Known Breakout by Google’s AI — Wall Street Journal Technology
- Google Joins OpenAI, Anthropic, Meta in Disclosing AI Hacks — Bloomberg AI
- Introducing Kimi K3 on Amazon Bedrock — AWS Machine Learning Blog
- Introducing Amazon SageMaker HyperPod Inference Gateway — AWS Machine Learning Blog
- Introducing Astra for Law — OpenAI News
- Newsom signs executive order to explore new AI rules, consider ‘kill switch’ — Politico Technology
- Anthropic, OpenAI, SpaceXAI, Google sued over call to ‘pace’ AI development — Politico Technology
- Sources: Anthropic considers releasing a new AI model to counter OpenAI's momentum since Astra's launch, ahead of an IPO and after Amodei's call for a slowdown (Reuters) — Techmeme
Get the daily brief of stories like this at 6:30 every morning →