Text Classification
Transformers
ONNX
Safetensors
English
bert
cybersecurity
phishing-detection
nlp
social-engineering
text-embeddings-inference
Instructions to use xynaxdev/ph5-text-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xynaxdev/ph5-text-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xynaxdev/ph5-text-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xynaxdev/ph5-text-bert") model = AutoModelForSequenceClassification.from_pretrained("xynaxdev/ph5-text-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model_quantized.onnx from xynaxdev/ph5-text-bert: direct link, hf CLI and curl.
- Browser
- Download file 110 MB
-
https://huggingface.co/xynaxdev/ph5-text-bert/resolve/main/model_quantized.onnx
- Command line
-
hf download hf://xynaxdev/ph5-text-bert/model_quantized.onnx
-
curl -L -o model_quantized.onnx https://huggingface.co/xynaxdev/ph5-text-bert/resolve/main/model_quantized.onnx
110 MB
- Xet hash:
- ba58759954402860ec81e9c52f41cedc3f393d59161d77284128a0378067ef36
- Size of remote file:
- 110 MB
- SHA256:
- 3460f989dbfff5e97d077542a298546783d0aacfff6c1333e16460646b448b18
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