Instructions to use Satish678/t5-large_PREFIX_TUNING_case2step with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Satish678/t5-large_PREFIX_TUNING_case2step with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("t5-large") model = PeftModel.from_pretrained(base_model, "Satish678/t5-large_PREFIX_TUNING_case2step") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from Satish678/t5-large_PREFIX_TUNING_case2step: direct link, hf CLI and curl.
- Browser
- Download file 3.93 MB
-
https://huggingface.co/Satish678/t5-large_PREFIX_TUNING_case2step/resolve/main/adapter_model.bin
- Command line
-
hf download hf://Satish678/t5-large_PREFIX_TUNING_case2step/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/Satish678/t5-large_PREFIX_TUNING_case2step/resolve/main/adapter_model.bin
3.93 MB
- Xet hash:
- 175240abee8bcf9b4df389d5f774e00198b3e592eceba7d19631d781be8a606c
- Size of remote file:
- 3.93 MB
- SHA256:
- 508e67079b61c3b96cede8b0f9a462a5662c4b9d8a430807f60ea9ce21d618bc
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