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:
- dd0073cf4291c55603aef455b00024ccd47a9a737b3ea6dd3641b4634a3de2f0
- Size of remote file:
- 180 kB
- SHA256:
- 236fe79b1613fe8d7cef439c389c3123f31e55226c7dcd04b904ce2ad0c5da9a
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