Instructions to use LoftQ/bart-large-bit2-rank32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use LoftQ/bart-large-bit2-rank32 with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("facebook/bart-large") model = PeftModel.from_pretrained(base_model, "LoftQ/bart-large-bit2-rank32") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 51239148fe5bfea140a1fee66d4201359d9b3a03dd8f77d808a9bc1c8a78b65d
- Size of remote file:
- 1.69 GB
- SHA256:
- 0525754d849231989a0daa993398353b50d861f520e9f756d27405afab240ec3
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