Instructions to use pcuenq/tiny-gemma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pcuenq/tiny-gemma with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="pcuenq/tiny-gemma")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("pcuenq/tiny-gemma") model = AutoModel.from_pretrained("pcuenq/tiny-gemma") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 19d8aa605691d301d0be4ed0e957836b81e6224a338db5bc8c66e73141bc68fd
- Size of remote file:
- 92.8 MB
- SHA256:
- 908ff340d0ff89dc08ba3fe86e73bad178cf1aea60636c4d6357a5684c7cffe1
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