Instructions to use debaterhub/ipda-debater-depth-lora-iter1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use debaterhub/ipda-debater-depth-lora-iter1 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/home/ubuntu/training_outputs/cx_training/merged") model = PeftModel.from_pretrained(base_model, "debaterhub/ipda-debater-depth-lora-iter1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0d4e107c2d924b9695f6eef8eb42fd08929f424bcb8ce3ed5206d86cc7d50fa0
- Size of remote file:
- 6.23 kB
- SHA256:
- 48cf6388bab606a77c431b785c07fd1027a188bc960effb51a33e81b47785eff
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.