Text Classification
Transformers
LiteRT
ONNX
Safetensors
English
bert
sms
sms-classification
clean-address
bert-base
msgsense
text-embeddings-inference
Instructions to use imShub10/msgsense-sms-bert-base-cleanaddr-fulldata-20260424 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use imShub10/msgsense-sms-bert-base-cleanaddr-fulldata-20260424 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="imShub10/msgsense-sms-bert-base-cleanaddr-fulldata-20260424")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("imShub10/msgsense-sms-bert-base-cleanaddr-fulldata-20260424") model = AutoModelForSequenceClassification.from_pretrained("imShub10/msgsense-sms-bert-base-cleanaddr-fulldata-20260424", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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