1from vllm import LLM, SamplingParams 2from vllm.utils import FlexibleArgumentParser 3 4 5def main(): 6 7 parser = FlexibleArgumentParser(description='AQLM ...

15 мар. 2024 г. · AQLM is a new weight-only post-training quantization (PTQ) algorithm that sets a new state-of-the-art for the 2 bit-per-parameter range.

A high-throughput and memory-efficient inference and serving engine for LLMs - vllm/examples/aqlm_example.py at main · vllm-project/vllm.

1import argparse 2 3from vllm import LLM, SamplingParams 4 5 6def main(): 7 8 parser = argparse.ArgumentParser(description='AQLM examples') 9 10 ...

Aqlm Example · Gradio OpenAI Chatbot Axtarishserver · Gradio Axtarishserver · Llava Example · Llava Next Example · LLM Engine Example · Lora With Quantization Inference ...

6 мая 2024 г. · We are excited to share a series of updates regarding AQLM quantization. We published more prequantized models, including Llama-3-70b and Command-R+.

Supported Hardware for Quantization Kernels#. The table below shows the compatibility of various quantization implementations with different hardware ...

vLLM is a fast and easy-to-use library for LLM inference and serving. vLLM is fast with: vLLM is flexible and easy to use with: vLLM Engine · vLLM Meetups · Speculative decoding in vLLM · Installation

We're on a journey to advance and democratize artificial intelligence through open source and open science.

17 сент. 2024 г. · Using the latest version of vllm 0.6.1.post2 throws Unsupported base layer: QKVParallelLinear(in_features=8192, output_features=10240, ...