Instructions to use Firoj112/KVASIR_4bit_quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Firoj112/KVASIR_4bit_quantized with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/root/.cache/modelscope/hub/models/google/paligemma-3b-pt-224") model = PeftModel.from_pretrained(base_model, "Firoj112/KVASIR_4bit_quantized") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1d4ec5ac87cdc9032af84e422434305926635b839ee8e1a8eacb5f41fb3d581d
- Size of remote file:
- 34.6 MB
- SHA256:
- 172fab587d68c56b63eb3620057c62dfd15e503079ff7fce584692e3fd5bf4da
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.