Instructions to use vimal52/Alpacabase_LoRa_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use vimal52/Alpacabase_LoRa_test with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-base") model = PeftModel.from_pretrained(base_model, "vimal52/Alpacabase_LoRa_test") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 32df74127dc78c1c69314f862d93c64eb6620fb7a3f8f2239ab8369d4b2390c6
- Size of remote file:
- 3.59 MB
- SHA256:
- 3612c5d23bcff0a076e258bbfa5439688ecf86a331a7f55d128f382e826c3934
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