Instructions to use hf-internal-testing/tiny-random-Starcoder2Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Starcoder2Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-Starcoder2Model")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-Starcoder2Model") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-Starcoder2Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4973d580922dbaf8e400beaafa27f6c8f2ce77e90f4100f4d9a8bf72ee94910b
- Size of remote file:
- 180 kB
- SHA256:
- d5f8bd7913e92ea7bc34473fc4361e34e9dbf0db436ac328d73501a062e05dea
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