Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use vat75/PhishGuard-AI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vat75/PhishGuard-AI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vat75/PhishGuard-AI")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vat75/PhishGuard-AI") model = AutoModelForSequenceClassification.from_pretrained("vat75/PhishGuard-AI") - Notebooks
- Google Colab
- Kaggle
PhishGuard-AI / runs /Apr25_00-26-07_8ac8e04da368 /events.out.tfevents.1777076768.8ac8e04da368.253.0
- Xet hash:
- f247561adaaee2d6e426dbc3173415b9e60112cc55f0fef5c4dc1cc84cc3e234
- Size of remote file:
- 10.6 kB
- SHA256:
- 38b219a22485e83190e1ef7a6c0372ae8c6f9246784689e40d0dd24a71122e67
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.