Instructions to use pcuenq/tiny-gemma-test3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pcuenq/tiny-gemma-test3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="pcuenq/tiny-gemma-test3")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("pcuenq/tiny-gemma-test3") model = AutoModel.from_pretrained("pcuenq/tiny-gemma-test3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2f9b9962740f14996fe1384ed88f39138322f017f14b8192abce8a472d35ff28
- Size of remote file:
- 92.8 MB
- SHA256:
- 18c39cf34a4f6eed0ef93f5235dfd5cbc3c44753fd211c6c0c21948a57ca5321
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