Two-Author Model Tech Report Praised as Dense: Pretraining to Downstream
antoine_chaffin · x · 2026-09-03
NVIDIA researcher Antoine Chaffin recommends a technical report authored by just two people (Tony Wu and Aurélien Lucchi), calling the quantity of work and detail mind-blowing.
The report digs into pretraining setups, efficiency design, and downstream tasks. Even the sections on retrieval — and the extensive exploration of the LI setup spanning multi-head dense/LI, pooling, quantization, and kernels — are remarkably dense.
He suggests it's worth a read for anyone interested in the covered topics and hopes the accompanying models prove as useful to the community as the report.
More from Models
- As Claude Goes Down, X User Jokes OpenAI Should Seize the Moment With a Surprise 'Astra' Release — kimmonismus · 2026-09-03
- User ditches GPT-5.6-sol for DeepSeek V4 Pro: 'feels like Opus 7.0 landed' — ryunuck · 2026-09-03
- Running DeepSeek-V4-Flash-Vision on dual RTX 6000: 350K context at 7 concurrent — DeedleDumbDee · 2026-09-03
- Redditor quips Google might as well open-source Gemini 3.1 Pro — Possible_Door_9719 · 2026-09-03
- Claude Max 20x User Burns Through Entire 5-Hour Session Quota in About 30 Minutes — NathanSRobinson · 2026-09-03
- Gemini 3.8 Flash reportedly lacks internet access and knows nothing of Google's own Antigravity — seybling · 2026-09-03