Instructions to use laquythang/e4c65784-ac5d-438c-9e1a-2ff5b592fad3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use laquythang/e4c65784-ac5d-438c-9e1a-2ff5b592fad3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Maykeye/TinyLLama-v0") model = PeftModel.from_pretrained(base_model, "laquythang/e4c65784-ac5d-438c-9e1a-2ff5b592fad3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c927bf430679c739d9033747218c06d0fed21e66a9ebf8cd0d45922aa1b49fb6
- Size of remote file:
- 768 kB
- SHA256:
- 4ec1241a27264a4a01bbb34044633f460a05839fdbbc3803c3ff89a4abcf4f49
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.