Instructions to use laquythang/65ec45c4-e0b8-4a8f-a971-035adc0edba0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use laquythang/65ec45c4-e0b8-4a8f-a971-035adc0edba0 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/zephyr-sft") model = PeftModel.from_pretrained(base_model, "laquythang/65ec45c4-e0b8-4a8f-a971-035adc0edba0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c936c801f7e36b9688f863b06e5c6c4c6ccff2988d3fb6081782d582b4842a7b
- Size of remote file:
- 83.9 MB
- SHA256:
- b777a07c82b513d4f1176fc2dc85d4acf0c1f3127b8cf3133b1574a0ffe64ae0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.