Instructions to use ZeroUniqueness/qlora-llama-2-13b-code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ZeroUniqueness/qlora-llama-2-13b-code with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/workspace/webui/models/TheBloke_Llama-2-13B-fp16") model = PeftModel.from_pretrained(base_model, "ZeroUniqueness/qlora-llama-2-13b-code") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fac307257b04b7a2f040cf8b9d33ebb18dca6440b60cb1c5f3931c46d716b8d7
- Size of remote file:
- 4.03 kB
- SHA256:
- 1c2f4cc723c65538de12d445f71a30b1610b702bfe771edb2385636bb8724bfd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.