Instructions to use hf-internal-testing/tiny-random-StableLmModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-StableLmModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-StableLmModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-StableLmModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-StableLmModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2ac54eb3e86730068302a5e4a49a5956ba655254cc3f887acdddca3705b68cdd
- Size of remote file:
- 455 kB
- SHA256:
- 0e801a783304c46e79c45baecb678f2a817d3d37a07676c04e8db61d9d95fecb
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