Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use casonshep/spam_message_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use casonshep/spam_message_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="casonshep/spam_message_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("casonshep/spam_message_classification") model = AutoModelForSequenceClassification.from_pretrained("casonshep/spam_message_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 30037d0f3ba07305f4e58cace182636f569d65cdfa5f912e4cbcf877a2c335ca
- Size of remote file:
- 268 MB
- SHA256:
- dee1133dec5a9329d9dcde6b127c55195b832432ab6ec9f7390cefc8e9ab70bc
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