device_map={"transformer.h.0":"cuda:0",# 第一部分放在GPU0"transformer.h.1":"cuda:1",# 第二部分放在GPU1#...根据模型结构继续分配}model=AutoModelForCausalLM.from_pretrained(model_dir,device_map=device_map) 三、总结 本文简要介绍了device_map="auto"等使用方法,多数情况下与CUDA_VISIBLE_DEVI...
python import os import torch from transformers import AutoTokenizer, AutoModelForCausalLM # 设置可见GPU os.environ['CUDA_VISIBLE_DEVICES'] = '0, 1' # 模型路径 model_path = "./model/chatglm2-6b" # 加载tokenizer tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True) ...
那么在命令行,可以使用:https:///tensorflow/nmt/issues/60 CUDA_VISIBLE_DEVICES=0 python -m nmt.nmt 1. 四、GPU动态增长 import keras.backend.tensorflow_backend as KTF import tensorflow as tf import os os.environ["CUDA_VISIBLE_DEVICES"] = "1" config = tf.ConfigProto() config.gpu_options.allo...
CUDA_VISIBLE_DEVICES=1,2 python test_device_map_pipelines.py --num_inference_steps=50 --do_device_map VAE: tensor([0.2964, 0.2983, 0.3008, 0.2917, 0.3213, 0.3174, 0.3298, 0.3298, 0.2352, 0.2367, 0.2539, 0.2510], device='cuda:0', dtype=torch.float16) We can see that the outputs are...
Can you also try your script withexport CUDA_VISIBLE_DEVICES=1instead ofexport CUDA_VISIBLE_DEVICES=0? Sorry, something went wrong. Copy link Author youngwoo-yooncommentedDec 26, 2022 Thanks for the quick replies. This is the result and it still doesn't look good. ...
python<<EOFimport pickle, torchwith open("file.pkl", "wb") as fd:pickle.dump(torch.zeros(10, device="cuda"), fd)torch.save(torch.ones(10, device="cuda"), 'file2.pkl')EOF#Disable CUDAexportCUDA_VISIBLE_DEVICES= python<<EOFimport torchprint(torch.load("file2.pkl", map_location=torc...