Posts by Inesh Chakrabarti
Quark Support for HuggingFace Diffusers and SVDQuant
- 06 August 2026
Diffusion models are heavy on memory and compute: a single text-to-image call runs a large transformer or UNet dozens of times. Quantization — storing weights (and sometimes activations) in low precision — is one of the most effective ways to cut both the memory footprint and the latency of these models.
Productionizing TurboQuant on AMD GPUs for KV-Cache-Bound LLM Inference
- 11 June 2026
*The first three authors (Chakrabarti, Limpus, Rana) contributed equally to this work.