Text Classification
Transformers
Safetensors
English
distilbert
spam-detection
nlp
text-embeddings-inference
Instructions to use Abdallah-Thuieb/distilbert-spam-classification-binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Abdallah-Thuieb/distilbert-spam-classification-binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Abdallah-Thuieb/distilbert-spam-classification-binary")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Abdallah-Thuieb/distilbert-spam-classification-binary") model = AutoModelForSequenceClassification.from_pretrained("Abdallah-Thuieb/distilbert-spam-classification-binary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from Abdallah-Thuieb/distilbert-spam-classification-binary: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/Abdallah-Thuieb/distilbert-spam-classification-binary/resolve/main/model.safetensors
- Command line
-
hf download hf://Abdallah-Thuieb/distilbert-spam-classification-binary/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Abdallah-Thuieb/distilbert-spam-classification-binary/resolve/main/model.safetensors
268 MB
- Xet hash:
- c7093595c6fa95487b76af2130b09fc31e1815ccc0a75a0b3217e8bc74258fa6
- Size of remote file:
- 268 MB
- SHA256:
- 1d97d924e18feafd6d9f706cc42f5517692a057eab96d84d7d6b51f064cb7cfa
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