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:
- b3ad6f4ed25a61ddbb148b1f1e9e519d809f3ff434d574dbad23d83de83ca831
- Size of remote file:
- 455 kB
- SHA256:
- eb026907072ec666065b2fefb0d4a04af3b1e4d6a953fa2b5224c32ac5755677
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