Instructions to use YuryCHep/FAKERDISTILBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YuryCHep/FAKERDISTILBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YuryCHep/FAKERDISTILBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YuryCHep/FAKERDISTILBERT") model = AutoModelForSequenceClassification.from_pretrained("YuryCHep/FAKERDISTILBERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ab5ce8d189d2d13d37ed9edb51645203ac9375cf7edcedee3d91013d4a38d414
- Size of remote file:
- 541 MB
- SHA256:
- 43870d23a70b8d07a130bbca2f8e9ae035358d3515c6f430053527cb915003f2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.