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:
- c97ac5c6275aadc2ee2904740e71a22a9a930b0a0c6855c2b734adef1d6e9ac5
- Size of remote file:
- 455 kB
- SHA256:
- f486c82b757b8ac0c59fd1fda79570e2b323b67605adead58d3e7a3d256f6f6d
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