class_docstr: Uses the CLIP transformer encoder for text (from Hugging Face)
class_docstr_tok: ["Uses","the","CLIP","transformer","encoder","for","text","(","from","Hugging","Face",")"]
code: def __init__(
      self,
      version="openai/clip-vit-large-patch14",
      device="cuda",
      max_length=77,
  ):
      super().__init__()
      self.tokenizer = CLIPTokenizer.from_pretrained(version)
      self.transformer = CLIPTextModel.from_pretrained(version)
      self.device = device
      self.max_length = max_length
      self.freeze()
  
imports: import torch
  import torch.nn
  from functools import partial
  import clip
  from einops import rearrange, repeat
  from transformers import CLIPTokenizer, CLIPTextModel
  import kornia
  from ldm.modules.x_transformer import Encoder, TransformerWrapper
label_desc: Use image node_id 1 to create a new FrozenCLIPEmbedder object from inherited base classes: AbstractEncoder with example: obj = FrozenCLIPEmbedder(version, device, max_length)