Instructions to use adrienbrdne/electra-problematic-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adrienbrdne/electra-problematic-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="adrienbrdne/electra-problematic-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("adrienbrdne/electra-problematic-classifier") model = AutoModelForSequenceClassification.from_pretrained("adrienbrdne/electra-problematic-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c44d640bce7c9d8c2223dc2ddef62b987de20d8ee6d41237e1c0a75daf189f13
- Size of remote file:
- 438 MB
- SHA256:
- 2fe053b8931f0b26e382ce5b798f6e3955bec1335f501f14364266b2434d757b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.