Instructions to use lorahub/flan_t5_large-adversarial_qa_dbidaf_question_context_answer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use lorahub/flan_t5_large-adversarial_qa_dbidaf_question_context_answer with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-large") model = PeftModel.from_pretrained(base_model, "lorahub/flan_t5_large-adversarial_qa_dbidaf_question_context_answer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9929260c3501fbbe1c04b8058b52bb4a3677e0c8210d478af97ffd2b597736e3
- Size of remote file:
- 19 MB
- SHA256:
- 9a3c1f8d77f8b1a92dc17eb073854190db3b62a37d6d9c9c6ff2c84be61bbc9a
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