Instructions to use TinyPixel/qlora-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use TinyPixel/qlora-2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("h2oai/h2o-danube-1.8b-base") model = PeftModel.from_pretrained(base_model, "TinyPixel/qlora-2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd91ee8a5e70f3945b2f8006b13985385fc9a39454620a3537ef9a039786f1fe
- Size of remote file:
- 554 MB
- SHA256:
- 15b2812c80d28fe92fd38c445c8df351ef14d2298f1058aba8d344b1b9bdf179
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.