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:
- 08ebd74976a9f58b7611eb9e7eab2140b7f60fb5931ad0199879e370dcec26ab
- Size of remote file:
- 455 kB
- SHA256:
- 6bab0288160080231f62a7a87342e08b8577fbaf323bca5cd773f10a84e1ba4f
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