Instructions to use hf-internal-testing/tiny-random-SeamlessM4Tv2Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SeamlessM4Tv2Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-SeamlessM4Tv2Model")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-SeamlessM4Tv2Model") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-SeamlessM4Tv2Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c25456f47e7ad66db0ab4fbb0ef48e4dcfad4dafdeec76d0da61d88ae8cfdf50
- Size of remote file:
- 338 kB
- SHA256:
- c6a0a9ca14631f6081bcfce5f23322017458767c8241430be4ba799a453e24f6
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