Instructions to use UlukaDev/bitnet-roman-numeral-expert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use UlukaDev/bitnet-roman-numeral-expert with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/bitnet-b1.58-2B-4T-bf16") model = PeftModel.from_pretrained(base_model, "UlukaDev/bitnet-roman-numeral-expert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0a314d0612c70111a06bd11a4b14a75e32f8decaab9f63d74b0762e70e347387
- Size of remote file:
- 17.2 MB
- SHA256:
- 8fc5ed64d17c57f61c0ef996ac8b3a8918e7d406866cc4a0292d362a31a217e4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.