Helen Zhao
Helen Zhao's contributions
Article
Optimized support for Open NVIDIA Nemotron 3.5 Super VL
Eldar Kurtić
+3
Double Nemotron 3.5 Super VL inference throughput on NVIDIA Hopper GPUs. Learn how FP8 quantization and DSpark speculative decoding boost speed and accuracy.
Article
Speeding up LLM inference with P-EAGLE in vLLM Speculators
Helen Zhao
+3
Learn how P-EAGLE in Speculators v0.6.0 uses parallel drafting to reduce LLM latency. Train and deploy custom draft models with this step-by-step guide.
Article
Speculators v0.5.0: DFlash support and online training
Helen Zhao
+2
Speculators v0.5.0 introduces DFlash support, enabling single-pass draft token generation with block diffusion for more efficient speculative decoding workflows. The release also adds unified online and offline training through vLLM’s native hidden states extraction system, improving training flexibility, version stability, and production readiness.
Article
Speculators: Standardized, production-ready speculative decoding
Alexandre Marques
+7
Speculators standardizes speculative decoding for large language models, with a unified Hugging Face format, vLLM integration, and more.
Article
LLM Compressor 0.7.0 release recap
Dipika Sikka
+3
LLM Compressor 0.7.0 brings Hadamard transforms for better accuracy, mixed-precision FP4/FP8, and calibration-free block quantization for efficient compression.
Optimized support for Open NVIDIA Nemotron 3.5 Super VL
Double Nemotron 3.5 Super VL inference throughput on NVIDIA Hopper GPUs. Learn how FP8 quantization and DSpark speculative decoding boost speed and accuracy.
Speeding up LLM inference with P-EAGLE in vLLM Speculators
Learn how P-EAGLE in Speculators v0.6.0 uses parallel drafting to reduce LLM latency. Train and deploy custom draft models with this step-by-step guide.
Speculators v0.5.0: DFlash support and online training
Speculators v0.5.0 introduces DFlash support, enabling single-pass draft token generation with block diffusion for more efficient speculative decoding workflows. The release also adds unified online and offline training through vLLM’s native hidden states extraction system, improving training flexibility, version stability, and production readiness.
Speculators: Standardized, production-ready speculative decoding
Speculators standardizes speculative decoding for large language models, with a unified Hugging Face format, vLLM integration, and more.
LLM Compressor 0.7.0 release recap
LLM Compressor 0.7.0 brings Hadamard transforms for better accuracy, mixed-precision FP4/FP8, and calibration-free block quantization for efficient compression.