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:
- a785e23950ad3cfc5daca6c78151c6f2b1610dbb43d1a291d4ec7d68d642c8bd
- Size of remote file:
- 338 kB
- SHA256:
- 2f31e4870cc6a28427e07821c105e45eddad38f9468c3e8b9fa07ef900ffca3c
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