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:
- f10b4a80d713a166f120fb932ab8fb25baf7931544535d26d1ab5af6a69ba463
- Size of remote file:
- 455 kB
- SHA256:
- 9f570fb11c6d9cb578d10d25b547e983b13a7943ab812605c1551f1c26608ea8
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