#PyTorchLightning 还有这么多好用的项目
尤其这里,它们所有的项目都值得好好的关注下。
https://github.com/PyTorchLightning
Flexible interface for high-performance research using SOTA Transformers leveraging Pytorch Lightning, Transformers, and Hydra.
基本是把各种nlp项目实现了一遍,拿来或者参考都不错。
Using Lightning-Transformers
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Task
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python train.py task=nlp/language_modeling dataset=nlp/language_modeling/wikitext trainer.gpus=1 training.batch_size=8
python train.py task=nlp/multiple_choice dataset=nlp/multiple_choice/race trainer.gpus=1
python train.py task=nlp/question_answering dataset=nlp/question_answering/squad trainer.gpus=1
python train.py task=nlp/summarization dataset=nlp/summarization/xsum trainer.gpus=1
python train.py task=nlp/text_classification dataset=nlp/text_classification/emotion trainer.gpus=1
python train.py task=nlp/token_classification dataset=nlp/token_classification/conll trainer.gpus=1
python train.py task=nlp/translation dataset=nlp/translation/wmt16 trainer.gpus=1
https://github.com/PyTorchLightning/lightning-transformers
kaggle添加验证信息等
import wandb
from kaggle_secrets import UserSecretsClient
user_secrets = UserSecretsClient()
personal_key_for_api = user_secrets.get_secret("wandb-key")
! wandb login $personal_key_for_api
https://github.com/ultralytics/yolov5/issues/1372