Text Classification
Transformers
Safetensors
PyTorch
English
tiny_log_classifier
cybersecurity
blue-team
log-analysis
custom-code
custom_code
Instructions to use mozarilla/tiny-blue-log-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mozarilla/tiny-blue-log-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mozarilla/tiny-blue-log-classifier", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("mozarilla/tiny-blue-log-classifier", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "TinyLogForSequenceClassification" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_tiny_log.TinyLogConfig", | |
| "AutoModelForSequenceClassification": "modeling_tiny_log.TinyLogForSequenceClassification" | |
| }, | |
| "hidden_size": 16, | |
| "id2label": { | |
| "0": "BENIGN", | |
| "1": "SUSPICIOUS" | |
| }, | |
| "label2id": { | |
| "BENIGN": 0, | |
| "SUSPICIOUS": 1 | |
| }, | |
| "max_position_embeddings": 96, | |
| "model_type": "tiny_log_classifier", | |
| "num_labels": 2, | |
| "pad_token_id": 0, | |
| "vocab_size": 1024 | |
| } | |