Text Classification
Transformers
PyTorch
TensorBoard
English
distilbert
sms
spam
detection
text-embeddings-inference
Instructions to use akuysal/English-SMS-classification-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akuysal/English-SMS-classification-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="akuysal/English-SMS-classification-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("akuysal/English-SMS-classification-model") model = AutoModelForSequenceClassification.from_pretrained("akuysal/English-SMS-classification-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 26c12064980c2157155a440ee35c517083c597325bee940a80f923a5a60db348
- Size of remote file:
- 268 MB
- SHA256:
- e83e321de538f0d8b8861090181fbe5d0f8095c07fa5423628c7ae4aaba1085a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.