class_docstr: Simple sentiment analysis model.
class_docstr_tok: ["Simple","sentiment","analysis","model","."]
code: def __init__(self, model_name_or_path):
      self.tokenizer = transformers.AutoTokenizer.from_pretrained(
          model_name_or_path
      )
      model_config = transformers.AutoConfig.from_pretrained(
          model_name_or_path,
          num_labels=2,
          output_hidden_states=True,
          output_attentions=True,
      )
      # This is a just a regular PyTorch model.
      self.model = _from_pretrained(
          transformers.AutoModelForSequenceClassification,
          model_name_or_path,
          config=model_config,
      )
      self.model.eval()
  
imports: from collections.abc import Sequence
  import sys
  from typing import Optional
  from absl import app
  from absl import flags
  from absl import logging
  from lit_nlp import dev_server
  from lit_nlp import server_flags
  from lit_nlp.api import model
  from lit_nlp.api import types
  from lit_nlp.examples.datasets import glue
  from lit_nlp.lib import file_cache
  from lit_nlp.lib import utils
  import torch
  import transformers
label_desc: Use image node_id 1 to create a new SimpleSentimentModel object from inherited base classes: lit_model with example: obj = SimpleSentimentModel(model_name_or_path)