Instructions to use demohong/57073731-d0b8-4a46-998c-f0b84da1056b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use demohong/57073731-d0b8-4a46-998c-f0b84da1056b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("lmsys/vicuna-13b-v1.5") model = PeftModel.from_pretrained(base_model, "demohong/57073731-d0b8-4a46-998c-f0b84da1056b") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fb7c5e8ef58c0f5637df20dc71d744281d44fa73ea5bd66f68e4a2cf68bf113f
- Size of remote file:
- 125 MB
- SHA256:
- 2bf8c81bedbadd3f5cf842ebfc84361ad95d0981d001105f26825e9a6a90539a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.