Instructions to use dzanbek/5bad54b6-e7b2-43d8-bb2e-cbc5d064f10c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dzanbek/5bad54b6-e7b2-43d8-bb2e-cbc5d064f10c with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("openlm-research/open_llama_3b") model = PeftModel.from_pretrained(base_model, "dzanbek/5bad54b6-e7b2-43d8-bb2e-cbc5d064f10c") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec8da133b6fafd25404bc2b0745f842aa88fdede6f66f11c7b4d63aea96d0400
- Size of remote file:
- 102 MB
- SHA256:
- 909911d2e738566799fba9567b149e5f9b576e2bf74dc47212ec2aae2119e4f0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.