Instructions to use SniiKz/Test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use SniiKz/Test with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("bigscience/bloom-3b") model = PeftModel.from_pretrained(base_model, "SniiKz/Test") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fbed674d4671f669d97c10c7908ec199b2b8599412b2e31dd4f31a4d7a77352f
- Size of remote file:
- 19.7 MB
- SHA256:
- 4ff2d3e7e0b1709e8f946db8a05c615e9e43af4077352078203ca80478143ac1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.