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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e12899495cb1022b4a39b56b96a316d01fea3334e316cafe7be6cba3c4c28c92
- Size of remote file:
- 38.5 kB
- SHA256:
- 4b2813cbfbdcf419a4d75745cbc0ff0bc49a111ee0e856dad44fd131141e008e
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