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:
- 51c837e6a7a157cb58912b78e3b8ba3196a23ddd7cb5914018e1e52f8a13dabb
- Size of remote file:
- 180 kB
- SHA256:
- 5f57569e08b506b9fae3de47a60faaa299f476eb1fbd94cf138fb2f8526eaa42
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