Text Classification
Transformers
Safetensors
multilingual
distilbert
phishing
email-security
text-embeddings-inference
Instructions to use eugenioderodev/fishstop-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eugenioderodev/fishstop-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="eugenioderodev/fishstop-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("eugenioderodev/fishstop-bert") model = AutoModelForSequenceClassification.from_pretrained("eugenioderodev/fishstop-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "dataset_sha256": "cef3877ed1eb371c62a3ce1a9e9e43ac72765a8ddda34eaa51f97bc58576d7ab", | |
| "base_model": "distilbert/distilbert-base-multilingual-cased", | |
| "epochs": 4, | |
| "temperature": 1.789758324623108, | |
| "threshold": 0.05, | |
| "test": { | |
| "accuracy": 0.9907079646017699, | |
| "f1": 0.9932885906040269, | |
| "precision": 0.9974326059050064, | |
| "recall": 0.9891788669637174 | |
| } | |
| } |