Text Classification
Transformers
TensorBoard
Safetensors
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use redblackbird/malware-id-bert-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use redblackbird/malware-id-bert-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="redblackbird/malware-id-bert-2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("redblackbird/malware-id-bert-2") model = AutoModelForSequenceClassification.from_pretrained("redblackbird/malware-id-bert-2") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Text Classification
Validation Metrics
loss: 0.7463629841804504
f1_macro: 0.471868840030326
f1_micro: 0.712253829321663
f1_weighted: 0.6488788212341754
precision_macro: 0.5558364938895912
precision_micro: 0.712253829321663
precision_weighted: 0.6886706852528584
recall_macro: 0.48134777376654636
recall_micro: 0.712253829321663
recall_weighted: 0.712253829321663
accuracy: 0.712253829321663
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