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:
- 875462dbb84265c66d7828222d5838a2a6d9f5a3f48192a7e8427d9ee7a03c1d
- Size of remote file:
- 173 kB
- SHA256:
- 6a8460ebcb769e88d01b6192cc066f4e0cd2ddf33ce6cc2b173955fbc2048c9e
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