Instructions to use Elegbede/Distilbert_FInetuned_For_Text_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Elegbede/Distilbert_FInetuned_For_Text_Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Elegbede/Distilbert_FInetuned_For_Text_Classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Elegbede/Distilbert_FInetuned_For_Text_Classification") model = AutoModelForSequenceClassification.from_pretrained("Elegbede/Distilbert_FInetuned_For_Text_Classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1ff71740658ecdebd186ace803dc0947462d5bd084eef4396dc69400cd01fea0
- Size of remote file:
- 268 MB
- SHA256:
- e905c1ce0c5db26f0d204493256af44c787a4dadaa7ad00cae5fe50ab4c4f8e0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.