Instructions to use greatakela/multilabel_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use greatakela/multilabel_classification with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("mistralai/Mistral-7B-v0.1") model = PeftModel.from_pretrained(base_model, "greatakela/multilabel_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3fd8caf84f8162d8eded457fe690af13cbd4656afc793d5dc73bf7d2527265f1
- Size of remote file:
- 4.73 kB
- SHA256:
- 9f734e3fd21d71e9ec6c6b7458c26eec1427928af43b1c82a711258f85e90d45
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.