Instructions to use pcuenq/tiny-gemma-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pcuenq/tiny-gemma-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="pcuenq/tiny-gemma-test")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("pcuenq/tiny-gemma-test") model = AutoModel.from_pretrained("pcuenq/tiny-gemma-test") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8200080518ad8cdd2089fdef7ed2aa8a116097049b40a8cfcb2ba30c9a5f31d6
- Size of remote file:
- 92.8 MB
- SHA256:
- 2fec82c9d60bbbb6d967546e86ffbd7b6fea84c3bc1634a062d213516defdf92
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