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:
- 3f1ff231b9789a11540c52a8b1b32ef4603fb31e82ff2fd157b5a785b5ad0e52
- Size of remote file:
- 180 kB
- SHA256:
- c3ded85c7844bfc93607e1d4305eca74b271f7594638c8bc0b159631a088bec3
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