Instructions to use hf-internal-testing/tiny-random-SeamlessM4Tv2ForSpeechToText with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SeamlessM4Tv2ForSpeechToText with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hf-internal-testing/tiny-random-SeamlessM4Tv2ForSpeechToText")# Load model directly from transformers import AutoTokenizer, AutoModelForSpeechSeq2Seq tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-SeamlessM4Tv2ForSpeechToText") model = AutoModelForSpeechSeq2Seq.from_pretrained("hf-internal-testing/tiny-random-SeamlessM4Tv2ForSpeechToText") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3fa9b7e788339284d7a68bf1e170b791bcf8f0b4cb299c053e81a38b39066c9d
- Size of remote file:
- 38.5 kB
- SHA256:
- aa245d0aa4e3dfba16a81f9e11779c1bdf03ec6b92715c938e7b5b242674c636
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