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:
- 2f11a28fd60a842534167509727f9c49291e6fe41d0d8ba050290af4f58cfc13
- Size of remote file:
- 173 kB
- SHA256:
- a7f6a4a908a3ac1a9104461692bd96bb21b12bea3ba9dd1cfa9d8ea4f949d651
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