Automatic Speech Recognition
Transformers
PyTorch
English
German
speech-encoder-decoder
audio
speech-translation
speech2text2
Instructions to use facebook/s2t-wav2vec2-large-en-de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/s2t-wav2vec2-large-en-de with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="facebook/s2t-wav2vec2-large-en-de")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSpeechSeq2Seq tokenizer = AutoTokenizer.from_pretrained("facebook/s2t-wav2vec2-large-en-de") model = AutoModelForSpeechSeq2Seq.from_pretrained("facebook/s2t-wav2vec2-large-en-de", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from facebook/s2t-wav2vec2-large-en-de: direct link, hf CLI and curl.
- Browser
- Download file 1.33 GB
-
https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://facebook/s2t-wav2vec2-large-en-de/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/pytorch_model.bin
1.33 GB
- Xet hash:
- 7a1fb03be06d72b98b3c1fe2667381704e559bb2f5c11aa9d9ef5659fd72c2ed
- Size of remote file:
- 1.33 GB
- SHA256:
- f20c40dcd3471e85e94b0721a6ca524f98660d5f9ac850220712b0a17ac1001e
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