Text Classification
Transformers
PyTorch
ONNX
Safetensors
English
bert
anti-spam
spam
text-embeddings-inference
Instructions to use Titeiiko/OTIS-Official-Spam-Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Titeiiko/OTIS-Official-Spam-Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Titeiiko/OTIS-Official-Spam-Model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Titeiiko/OTIS-Official-Spam-Model") model = AutoModelForSequenceClassification.from_pretrained("Titeiiko/OTIS-Official-Spam-Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Titeiiko/OTIS-Official-Spam-Model: direct link, hf CLI and curl.
- Browser
- Download file 17.6 MB
-
https://huggingface.co/Titeiiko/OTIS-Official-Spam-Model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Titeiiko/OTIS-Official-Spam-Model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Titeiiko/OTIS-Official-Spam-Model/resolve/main/pytorch_model.bin
17.6 MB
- Xet hash:
- bcb9dbb0b54bbf64492fb2412444bb9c353b1c89188db6880b77b5270929762c
- Size of remote file:
- 17.6 MB
- SHA256:
- 834c4b5dbc4a8aa3cbe5b56e380932c0e152e43ceeaf219a36ae98d66fbbfacb
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