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:
- 7cfe740f62ad309f6ca169667e6f23f343d09a601d2ca906cb9ee2031d1192df
- Size of remote file:
- 38.5 kB
- SHA256:
- bc9e0edf7c3d16911db163e89add52e61b2b7f027cec21dbd49e6b4c5743d1dc
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