Instructions to use lorahub/flan_t5_large-adversarial_qa_dbert_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_dbert_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_dbert_question_context_answer") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Upload tokenizer.json with huggingface_hub
5567734 -
Upload adapter_model.bin with huggingface_hub
c501e7e -
Upload adapter_config.json with huggingface_hub
7ecee2e -
Upload tokenizer_config.json with huggingface_hub
789e905 -
Upload README.md with huggingface_hub
811c3b6 -
Upload special_tokens_map.json with huggingface_hub
d6d7179 -
initial commit
Qian Liu163c184