# https://github.com/vllm-project/vllm/tree/v0.2.7/vllm/entrypoints/llm.pyclassLLM:defgenerate(self,prompts:Optional[Union[str,List[str]]]=None,sampling_params:Optional[SamplingParams]=None,prompt_token_ids:Optional[List[List[int]]]=None,use_tqdm:bool=True,)->List[RequestOutput]:"""Gene...
教程链接:https://go.openbayes.com/vSLNi 使用云平台:OpenBayes http://openbayes.com/console/signup?r=sony_0m6v 登录OpenBayes.com,在「公共教程」页面,选择「AlphaFold3 蛋白质预测 Demo」教程。 页面跳转后,点击右上角「克隆」,将该教程克隆至自己的容器中。 选择「NVIDIA GeForce RTX 4090」以及「vLLM」...
vllm.SamplingParams( n=1, # Number of output sequences to return for each prompt. top_p=0.9, # Float that controls the cumulative probability of the top tokens to consider. temperature=0, # randomness of the sampling seed=777, # Seed for reprod...
import time from tqdm import tqdm from transformers import AutoTokenizer 然后加载模型并在数据集的一小部分上生成它的输出。 dataset = load_dataset("akemiH/MedQA-Reason", split="train").select(range(10)) prompts = [] for sample in dataset: prompts.append(sample) sampling_params = SamplingParams...
!pip install transformers scipyfromvllmimportLLM, SamplingParamsfromdatasetsimportload_datasetimporttimefromtqdmimporttqdmfromtransformersimportAutoTokenizer 然后加载模型并在数据集的一小部分上生成它的输出。 dataset = load_dataset("akemiH/MedQA-Reason",split="train").select(range(10)) ...
from tqdm import tqdm from transformers import AutoTokenizer 然后加载模型并在数据集的一小部分上生成它的输出。 dataset = load_dataset("akemiH/MedQA-Reason", split="train").select(range(10)) prompts = [] for sample in dataset: prompts.append(sample) ...
Seems like use_tqdm option is not available yet ? thangld201 closed this as completed Dec 18, 2024 Member DarkLight1337 commented Dec 18, 2024 @DarkLight1337 Thank you for your quick reply! I converted the messages to use with LLM.beam_search now. Seems like use_tqdm option is not ...
outputs = self._run_engine_embed(use_tqdm=use_tqdm) return outputs run_engine_embed() Astep_embed()method doesn't need to execute while inwhile. def _run_engine_embed( self, *, use_tqdm: bool ) -> List[Union[RequestOutput, EmbeddingRequestOutput]]: ...
Requires: aiohttp, cmake, fastapi, filelock, lm-format-enforcer, ninja, numpy, nvidia-ml-py, openai, outlines, pillow, prometheus-client, prometheus-fastapi-instrumentator, psutil, py-cpuinfo, pydantic, ray, requests, sentencepiece, tiktoken, tokenizers, torch, torchvision, tqdm, transformers, ...
# Maximum numberoftokens to generate per output sequence.logits_processors=logits_processors,logprobs=5),use_tqdm=True)end=time()elapsed=(end-start)/60.#minutesprint(f"Inference of {VALIDATE} samples took {elapsed} minutes!")submit=25_000/128*elapsed/60print(f"Submit will take {submit} ...