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:
- a5d6329eb8d2fce75b8248e977d62e5bcb4f5b5251421a10c0ad5049e7353551
- Size of remote file:
- 5.11 kB
- SHA256:
- a7512fdf802073a1d66b7d5066bb5aa908d6ccb23713970fd06f27b7d37ae6a7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.