Instructions to use pcuenq/tiny-gemma-test2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pcuenq/tiny-gemma-test2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="pcuenq/tiny-gemma-test2")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("pcuenq/tiny-gemma-test2") model = AutoModel.from_pretrained("pcuenq/tiny-gemma-test2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3ba8c0ed3d7ef580046170277d78b552b7b5e3774e73b6b60b4ccc989cb6f79e
- Size of remote file:
- 92.8 MB
- SHA256:
- c4df6767f58e4ef4ba7ad747e37e75591f281e3ad3142694e759a29bccbed5d1
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