Instructions to use dzanbek/9ed1b4db-6ea4-42ca-8053-0c2dabf620dc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dzanbek/9ed1b4db-6ea4-42ca-8053-0c2dabf620dc with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/tinyllama") model = PeftModel.from_pretrained(base_model, "dzanbek/9ed1b4db-6ea4-42ca-8053-0c2dabf620dc") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 757b0d0ea1c3414ad5fd47bc5975a371e861d90f44f8c57925f2446bbe18838b
- Size of remote file:
- 14.2 kB
- SHA256:
- ea30508b2168921b3e75386a046978772f5cbc66bbd566c5d99dd61ea40c26f1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.