Instructions to use caffeic/lora-flan-5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use caffeic/lora-flan-5-small with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-small") model = PeftModel.from_pretrained(base_model, "caffeic/lora-flan-5-small") - Transformers
How to use caffeic/lora-flan-5-small with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("caffeic/lora-flan-5-small", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0b27f3679a98bd6259b330dbee7cf741ac16f34b1cde982bb37721bc10f39893
- Size of remote file:
- 5.39 kB
- SHA256:
- 8eb5c2622e2cd0053d806c9dfab961ef74f9d4da3e88f2f25df00913cf5c356e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.