- Are you pursuing a PhD and are you interested in working on efficiency of LLMs/LVMs? Then join our model efficiency team in #QualcommAIResearch for an internship! Apply below, we have openings for 2025 as well as autumn/winter 2024. careers.qualcomm.com/careers/job/44…
- Interested in boosting quantized LLM performance with QAT? Check out our latest work on Low-Rank Quantization-Aware Training (LR-QAT) which can train 7B LLMs on a single consumer-grade GPU with just 24GB of memory. New work with @yell1337 and @delchia arxiv.org/abs/2406.06385
- I'm excited that our paper 'The LLM Surgeon' got accepted at #ICLR2024. This is work by @tychovdo during his internship at #QualcommAIResearch in collaboration with @martvanbaalen, @TiRune and @y_m_asano. Check out the thread below for more details.👇⭐️New paper ⭐️ Excited to share 'The LLM Surgeon', accepted at ICLR 2024. We obtain SOTA pruning performance and even demonstrate structured LLM pruning of full rows and cols. Direct practical impact enabling compression up to 20-30% with negligible loss in performance.🧵1/9👇
- This week I’m at #NeurIPS2023 to present our recent model efficiency research: 1) Pruning vs Quantization: Which is Better?, w/ A Kuzmin, @martvanbaalen, A Behboodi, @TiRune 2) Quantizable Transformers: Removing Outliers by Helping Attention Heads do Nothing, w/ @yell1337,@TiRune
