Text Classification
Transformers
ONNX
Safetensors
English
distilbert
cybersecurity
phishing-detection
url-classification
network-security
text-embeddings-inference
Instructions to use xynaxdev/ph5-url-distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xynaxdev/ph5-url-distilbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xynaxdev/ph5-url-distilbert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xynaxdev/ph5-url-distilbert") model = AutoModelForSequenceClassification.from_pretrained("xynaxdev/ph5-url-distilbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model_quantized.onnx from xynaxdev/ph5-url-distilbert: direct link, hf CLI and curl.
- Browser
- Download file 67.4 MB
-
https://huggingface.co/xynaxdev/ph5-url-distilbert/resolve/main/model_quantized.onnx
- Command line
-
hf download hf://xynaxdev/ph5-url-distilbert/model_quantized.onnx
-
curl -L -o model_quantized.onnx https://huggingface.co/xynaxdev/ph5-url-distilbert/resolve/main/model_quantized.onnx
67.4 MB
- Xet hash:
- c451b748901afcc2c7f4ce30697be6de9a75cdac8472c797311780182c1dd520
- Size of remote file:
- 67.4 MB
- SHA256:
- 4fdc66b745dad0fc4c27d929a310adeef0a7107b15e971ceb2ab986d3f484ce0
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