Instructions to use vimal52/Flant5_base_finetune_QLoRa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use vimal52/Flant5_base_finetune_QLoRa 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/Flant5_base_finetune_QLoRa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eb6b5ede83a58dd847caf4af2930d054dace8de0a6cf803db4e7055d55ede679
- Size of remote file:
- 3.59 MB
- SHA256:
- 1fae06c02cfccadea8e6270776bd3d6eaa7ebbf4eccc04c712f360924ecdc86d
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