```python
from datasets import load_dataset
from transformers import pipeline
librispeech_en = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")
asr = pipeline(
...     "automatic-speech-recognition",
...     model="facebook/s2t-wav2vec2-large-en-de",
...     feature_extractor="facebook/s2t-wav2vec2-large-en-de",
... )
translation_de = asr(librispeech_en[0]["file"])
```
See model hub to look for Speech2Text2 checkpoints.
Speech2Text2Config
[[autodoc]] Speech2Text2Config
Speech2TextTokenizer
[[autodoc]] Speech2Text2Tokenizer
    - batch_decode
    - decode
    - save_vocabulary
Speech2Text2Processor
[[autodoc]] Speech2Text2Processor
    - call
    - from_pretrained
    - save_pretrained
    - batch_decode
    - decode
    - as_target_processor
Speech2Text2ForCausalLM
