Instructions to use nellifurtado23/bcea018e-42ef-4852-b6bd-78bfb8bbe8eb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nellifurtado23/bcea018e-42ef-4852-b6bd-78bfb8bbe8eb with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen1.5-7B") model = PeftModel.from_pretrained(base_model, "nellifurtado23/bcea018e-42ef-4852-b6bd-78bfb8bbe8eb") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 06ae4905236f4cf140f7f30877ec3caa336fa637e8c4dcb95408d6883ee19c69
- Size of remote file:
- 7.1 kB
- SHA256:
- 482121f3f791555508fbaf815d82fdadd85cf70d42acd3f9c88ae856a0e6722f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.