Instructions to use lorahub/flan_t5_xl-wiqa_effect_with_string_answer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use lorahub/flan_t5_xl-wiqa_effect_with_string_answer with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-xl") model = PeftModel.from_pretrained(base_model, "lorahub/flan_t5_xl-wiqa_effect_with_string_answer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 60124146fa1b393829ebc1bed948fddc2091011da49108981b08622757271234
- Size of remote file:
- 37.9 MB
- SHA256:
- 51ed0a7fe29f8246357a93229cf2d9d453b07812a0a4ac1b59d8f705713c9670
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