Support mixed-precsion inference with vllm. Contribute to Qcompiler/vllm-mixed-precision development by creating an account on GitHub.
ValueError: paged_adamw_32bit is not a valid OptimizerNames, please select one of ['adamw_hf', 'adamw_torch', 'adamw_torch_fused', 'adamw_torch_xla', 'adamw_apex_fused', 'adafactor', 'adamw_bnb_8bit', 'adamw_anyprecision', 'sgd', 'adagrad'] ERROR:torch.distributed.elastic.multiproc...
(**inputs) File "<string>", line 126, in __init__ File "/usr/local/lib/python3.8/dist-packages/transformers/training_args.py", line 1499, in __post_init__ raise ValueError( ValueError: FP16 Mixed precision training with AMP or APEX (`--fp16`) and FP16 half precision evaluation ...
MixQ: Taming Dynamic Outliers in Mixed-Precision Quantization by Online Prediction We use mixed-precision GEMM for enhancing throughput. Please refer tohttps://github.com/Qcompiler/vllm-mixed-precisionfor end-to-end text generation. Comparision with AWQ ...
- TRT-LLM中的量化方法主要分为Mixed GEMM和Universal GEMM - PerChannel在推理时的计算流程简单,AWQ/GPTQ的权重量化是GroupWise的 - SmoothQuant不需要在计算GEMM之前做反量化,Scale可以在输出时应用 - 使用CUTLASS实现不同的量化技术需要考虑额外的CUDA核心指令和Shared Memory - 需要调整A/B矩阵的数据类型和位宽...
These initiatives underscore our commitment to pushing the boundaries of mixed-input quantization performance. By addressing these areas, we aim to make Machete an even more powerful and flexible tool for efficient LLM inference on NVIDIA Hopper GPUs and beyond. We're excited about the potent...
quantization suffer difficulties in quantizing LLMs accurately to such low-bit, but advanced methods remaining high-precision weights element-wisely are hard to realize their theoretical hardware efficiency. This paper presents a Salience-Driven Mixed-Precision Quantization scheme for LLMs, namely SliM-...
21 Aug 2024·Elias Frantar,Roberto L. Castro,Jiale Chen,Torsten Hoefler,Dan Alistarh· As inference on Large Language Models (LLMs) emerges as an important workload in machine learning applications, weight quantization has become a standard technique for efficient GPU deployment. Quantization not ...
In this study, we focus on a straightforward question: When aiming for a specific accuracy or perplexity target for low-precision quantization, how many high-precision numbers or calculations are required to preserve as we scale LLMs to larger sizes? We first introduce a critical metric named ...
Rules and membership functions must be adaptive to the changing environment in order to continue useful.Mr.Amit D.NaroteMr. LOBO. L.M.R.J