code: def __init__(self, batch_size, max_seq_length):
      # Model, tokenizer.
      self.model = transformers.BertModel.from_pretrained(
          "bert-large-cased"
      )
      self.tokenizer = transformers.AutoTokenizer.from_pretrained(
          "bert-large-cased", model_max_length=max_seq_length
      )
  
      # Feature extraction pipeline.
      self.pipe = MyFeatureExtractionPipeline(
          model=self.model,
          tokenizer=self.tokenizer,
          device=torch.cuda.current_device(),
          truncation=True,
          max_length=max_seq_length,
      )
  
      self.batch_size = batch_size
  
file_path: megatron-lm/tools/bert_embedding/huggingface.py
imports: import numpy
  import torch
  from tqdm import tqdm
  from .external_libs import transformers
label_desc: Use image node_id 1 to create a new HuggingfaceEmbedder object  with example: obj = HuggingfaceEmbedder(batch_size, max_seq_length)