Instructions to use hf-internal-testing/tiny-random-MambaModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MambaModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-MambaModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MambaModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-MambaModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2b3b836890629a093e2e10f555f3d2e077313e5db23b7fb9b302c561b105261a
- Size of remote file:
- 173 kB
- SHA256:
- e6804ed020187c6226089d5f02ddbac72615711f2e40aa73c769cc71fd817ed8
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