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:
- 26473d7f4ca1b83029f4f55b8a3804ee6b876933adca9f36cc793068ed87c1f7
- Size of remote file:
- 38.5 kB
- SHA256:
- 707789ea5f93fdfe892e4bc0f7af348774b6c67bfd7d4d6f4dea1f318ecf3a8c
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