Instructions to use asdc/gemma-8B-multilingual-temporal-expression-normalization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use asdc/gemma-8B-multilingual-temporal-expression-normalization with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-7b-it") model = PeftModel.from_pretrained(base_model, "asdc/gemma-8B-multilingual-temporal-expression-normalization") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7e2d204d74fa9c6bcec91a28d406d5c05a861246e3cecabc5df506fd0ccdbeeb
- Size of remote file:
- 54.7 MB
- SHA256:
- dab2b2da52f701a123fcb1116a82a34b693876fe8623b18653bceb44d09a8c85
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