Instructions to use abababab2003/trader-sft-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use abababab2003/trader-sft-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("C:\Users\user\Desktop\Trading-Agent\models\qwen3-8b") model = PeftModel.from_pretrained(base_model, "abababab2003/trader-sft-lora") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c9b52ce817ac7c2d9342c1f5456a3f885488abd61a2d1e252965b99fb4c805fe
- Size of remote file:
- 350 MB
- SHA256:
- 27efc8d64e86bdc283515fa3f60fef9676976f32faa05940ebe6c569ee9af41e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.