Instructions to use nhunglaaaaaaa/d46ff088-e9bb-4f03-bec0-0d2e7f5a079f with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhunglaaaaaaa/d46ff088-e9bb-4f03-bec0-0d2e7f5a079f with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Phi-3-mini-4k-instruct") model = PeftModel.from_pretrained(base_model, "nhunglaaaaaaa/d46ff088-e9bb-4f03-bec0-0d2e7f5a079f") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2d2e1be7e76c6ba3cfa4355260190f6154d981ff8b78afcec3da5aa059be1f4f
- Size of remote file:
- 6.78 kB
- SHA256:
- 99cf83aa8c59f38e26d2e6cbb64e96ce66d18410fe7fc4368dfff93928011572
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.