Accelerating Large Language Model Decoding with Speculative Sampling上图所示的例子中，draft model的参数...
(2)verification的时候不是使用greedy decoding,采用top-k 的log似然,然后使用验证值和top-k似然值之间的差值,这个差值会使用一个阈值来进行接受与否。这放宽了接受度的要求,会有一定的加速作用。 motivation: mask-predict 和Blockwise Decoding的区别在于: Blockwise Decoding共享了self-attention的参数,只是在最后加入...
[Speculative Decoding] Move indices to device before filtering output #10850 Merged DarkLight1337 merged 1 commit into vllm-project:main from zhengy001:zyang_spec Dec 3, 2024 Merged [Speculative Decoding] Move indices to device before filtering output #10850 DarkLight1337 merged 1 commit ...
We present Recurrent Drafter (ReDrafter), an advanced speculative decoding approach that achieves state-of-the-art speedup for large language models (LLMs) inference. The performance gains are driven by three key aspects: (1) leveraging a recurrent neural network (RNN) as the draft model conditi...
We then dig into a variety of techniques that can be used to accelerate inference such as KV compression, quantization, pruning, speculative decoding, and leveraging small language models (SLMs). We also discuss future directions for enabling on-device agentic experiences such as parallel generation...
"""Tests which cover integration of the speculative decoding framework with tensor parallelism. """ import pytest import torch from vllm.utils import is_hip from .conftest import run_greedy_equality_correctness_test @pytest.mark.skipif(torch.cuda.device_count() < 2, reason="Need at least 2 ...
NVIDIA TensorRT-LLM support for speculative decoding now provides over 3x the speedup in total token throughput. TensorRT-LLM is an open-source library that provides blazing-fast inference support for numerous popular large language models (LLMs) on NVIDIA GPUs. By adding support for speculative...
Figure 1: Generation on Qualcomm Cloud AI 100 Ultra (1) Baseline with FP16 weights (2) Acceleration with MX6 (3) Acceleration with MX6 and SpD Speculative Sampling (SpS), also known as Speculative Decoding (SpD), and weight compression throughMXFP6 microscaling format, are ...
Examples herein relate to decoding tokens using speculative decoding operations to decode tokens at an offset from a token decoded by a sequential decoding operation. At a checkpoin
Inference with Multimodal Large Language Models (MLLMs) is slow due to their large-language-model backbone which suffers from memory bandwidth bottleneck and generates tokens auto-regressively. In this paper, we explore the application of speculative decoding to enhance the inference efficiency of ML...