Instructions to use kamel-usp/jbcs2025_phi-4-phi4_classification_lora-C3-full_context with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kamel-usp/jbcs2025_phi-4-phi4_classification_lora-C3-full_context with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("microsoft/phi-4") model = PeftModel.from_pretrained(base_model, "kamel-usp/jbcs2025_phi-4-phi4_classification_lora-C3-full_context") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6f50c4b0a8efe5a3625d43097a18a664f70cecbdde615b44025f53f9044b47b2
- Size of remote file:
- 5.78 kB
- SHA256:
- a4b6d2f89ffe5b0d891e1ff62752e67d846de256e965ba910abe3a376664260c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.