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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 23eabbe374b23d80f229eb61208438b57ef3f13e37e3c34576fc81d038579203
- Size of remote file:
- 338 kB
- SHA256:
- 73c6a146bd58f8fce141dd652e04be75ade344e789b49c66440b0ab4dedf3ef9
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