Text Classification
Transformers
Safetensors
PyTorch
English
distilbert
spam-detection
sms
text-embeddings-inference
Instructions to use nagaananth/MLOPS_group-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nagaananth/MLOPS_group-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nagaananth/MLOPS_group-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nagaananth/MLOPS_group-v1") model = AutoModelForSequenceClassification.from_pretrained("nagaananth/MLOPS_group-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Group36 v1: trained DistilBERT SMS spam classifier
Browse files- README.md +9 -9
- model.safetensors +1 -1
README.md
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library_name: transformers
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license: mit
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pipeline_tag: text-classification
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library_name: transformers
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- text-classification
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- spam-detection
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- distilbert
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- sms
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license: mit
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datasets:
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- sms_spam
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- accuracy
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pipeline_tag: text-classification
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model.safetensors
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