Instructions to use Ngadou/bert-sms-spam-dectector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ngadou/bert-sms-spam-dectector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ngadou/bert-sms-spam-dectector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ngadou/bert-sms-spam-dectector") model = AutoModelForSequenceClassification.from_pretrained("Ngadou/bert-sms-spam-dectector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
a52c572
1
Parent(s): 5a88808
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (7931e1af15dc55b7b53c0c41773a67a70cdd4480)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:0f129e9e51648e785cc0ae1e76fc77d7a6ca0fcb56762fd0094e00cb94abea61
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size 437962832
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