Instructions to use vimal52/ab_q1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use vimal52/ab_q1 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/ab_q1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 76c95e11c8cfef68f479cb7afd7742d93c8e6d6ead67c853573fb1a63673fb53
- Size of remote file:
- 3.59 MB
- SHA256:
- 67981cdb9ebbdda45003c1fe5e2caa37a71393b8c5fb3cc1df37e65f2d0f7fb4
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