Instructions to use mockingmonkey/pali_result with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mockingmonkey/pali_result with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/paligemma-3b-mix-224") model = PeftModel.from_pretrained(base_model, "mockingmonkey/pali_result") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c0126ba4fee892d497299f05bf54d8ccad942eb664ef3522a264179b145e2525
- Size of remote file:
- 45.3 MB
- SHA256:
- 607be5a9e7a6b0ff96880d4306569e8aa0f10588081f05442cb3589035ba8d4d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.