```
If you don't find a model that has been pretrained on some data similar to yours, you will need to fine-tune a
pretrained model on your data. We provide example scripts to do so. Once you're done, don't forget
to share your fine-tuned model on the hub with the community, using this tutorial.
Under the hood: pretrained models
Let's now see what happens beneath the hood when using those pipelines.
As we saw, the model and tokenizer are created using the from_pretrained method:
```py
from transformers import AutoTokenizer, AutoModelForSequenceClassification
model_name = "distilbert-base-uncased-finetuned-sst-2-english"
pt_model = AutoModelForSequenceClassification.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)
===PT-TF-SPLIT===
from transformers import AutoTokenizer, TFAutoModelForSequenceClassification
