Question

我正在研究HuggingFace的转移学习功能（特别是用于命名实体识别的功能）。首先，我对变压器体系结构有些陌生。我在他们的网站上简要介绍了他们的示例：

from transformers import pipeline

nlp = pipeline("ner")

sequence = "Hugging Face Inc. is a company based in New York City. Its headquarters are in DUMBO, therefore very" \
       "close to the Manhattan Bridge which is visible from the window."

print(nlp(sequence))

我想做的是保存并在本地运行，而不必每次都下载“ ner”模型（大小超过1 GB）。在他们的文档中，我看到您可以使用“ pipeline.save_pretrained（）”函数将管道保存到本地文件夹。结果是将各种文件存储到特定的文件夹中。

我的问题是保存后如何将该模型重新加载到脚本中以继续进行分类？ “ pipeline.save_pretrained（）”的输出是多个文件。

这是我到目前为止尝试过的：

1：遵循有关管道的文档

pipe = transformers.TokenClassificationPipeline(model="pytorch_model.bin", tokenizer='tokenizer_config.json')

我得到的错误是：'str'对象没有属性“ config”

2：在ner上遵循HuggingFace示例：

from transformers import AutoModelForTokenClassification, AutoTokenizer
import torch

model = AutoModelForTokenClassification.from_pretrained("path to folder following .save_pretrained()")
tokenizer = AutoTokenizer.from_pretrained("path to folder following .save_pretrained()")

label_list = [
"O",       # Outside of a named entity
"B-MISC",  # Beginning of a miscellaneous entity right after another miscellaneous entity
"I-MISC",  # Miscellaneous entity
"B-PER",   # Beginning of a person's name right after another person's name
"I-PER",   # Person's name
"B-ORG",   # Beginning of an organisation right after another organisation
"I-ORG",   # Organisation
"B-LOC",   # Beginning of a location right after another location
"I-LOC"    # Location
]

sequence = "Hugging Face Inc. is a company based in New York City. Its headquarters are in DUMBO, therefore very" \
       "close to the Manhattan Bridge."

# Bit of a hack to get the tokens with the special tokens
tokens = tokenizer.tokenize(tokenizer.decode(tokenizer.encode(sequence)))
inputs = tokenizer.encode(sequence, return_tensors="pt")

outputs = model(inputs)[0]
predictions = torch.argmax(outputs, dim=2)

print([(token, label_list[prediction]) for token, prediction in zip(tokens, predictions[0].tolist())])

这会产生错误：列表索引超出范围

我还尝试仅打印出不返回令牌及其实体的文本格式的预测。

任何帮助将不胜感激！

将保存的NER加载回HuggingFace管道吗？

0 个答案: