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vLLM 4

vllm 활용해서 logit 추출 및 logprob, CoT, SC-CoT Inference 진행

class로 된 python이라 self나 다른 것 들이 붙어있긴 한데 적당히 보면 될 것 같습니다.기록 용이라....from datasets import load_from_disk, DatasetDictimport argparse, os, json, torch, itertools, math, refrom typing import List, Dict, Tuplefrom scipy.special import digammafrom vllm import LLM, SamplingParamsfrom collections import defaultdict, Counterfrom transformers import AutoTokenizerfrom setproctitle import setproctitle 일단 전부 ..

vllm 통해 reasoning path 데이터 만들기

지금 데이터를 늘리는 작업을 진행해서... 문서와 질문 그리고 정답을 통해 정답이 추론되는 과정을 만들려고 합니다.import jsonlinesimport jsonimport timefrom typing import Any, Optionalimport torchfrom transformers import AutoTokenizer # AutoModelForCausalLM 사용 안 함# vllm 임포트 (원래 주석처리 되어있던 부분을 활성화)from vllm import LLM, SamplingParams# from huggingface_hub import login# login("만약 access 필요한 모델이면, 토큰 발급받고 여기에 입력하삼!")import base64import timefrom ty..

Vllm을 활용한 빠른 Bench Mark Test 진행하기

https://huggingface.co/datasets/TIGER-Lab/MMLU-Pro TIGER-Lab/MMLU-Pro · Datasets at Hugging Face[ "Boycotts, Buyalls, Blockchain technology, Increased Sales", "Buycotts, Boycotts, Digital technology, Decreased Sales", "Boycotts, Buycotts, Digital technology, Decreased Sales", "Buycotts, Boycotts, Blockchain technology, Charitable donations", "Boycotthuggingface.co 이번에 만드는 모델을 평가하기 위해 벤치마크 중 하나인 ..

과제 겸 논문 리뷰 - Devils in Middle Layers of Large Vision-Language Models: Interpreting, Detecting and Mitigating Object Hallucinations via Attention Lens

https://arxiv.org/abs/2411.16724 Devils in Middle Layers of Large Vision-Language Models: Interpreting, Detecting and Mitigating Object Hallucinations via AttentHallucinations in Large Vision-Language Models (LVLMs) significantly undermine their reliability, motivating researchers to explore the causes of hallucination. However, most studies primarily focus on the language aspect rather than the..

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