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:
- 364164703cf1081686aa40c480633aac0657e54bb644862ccc12235a89e7b809
- Size of remote file:
- 180 kB
- SHA256:
- 31f7603f50d72cd89d184109ac6cfa75d568702ef3d0fa4124844f60ee5b37a7
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