Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use mcanoglu/microsoft-codebert-base-finetuned-defect-cwe-group-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mcanoglu/microsoft-codebert-base-finetuned-defect-cwe-group-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mcanoglu/microsoft-codebert-base-finetuned-defect-cwe-group-detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mcanoglu/microsoft-codebert-base-finetuned-defect-cwe-group-detection") model = AutoModelForSequenceClassification.from_pretrained("mcanoglu/microsoft-codebert-base-finetuned-defect-cwe-group-detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 77fae7d97ceac1b98f722b90c0b849925a592a0f583ca5846ec8a35ad1e345f4
- Size of remote file:
- 5.05 kB
- SHA256:
- f1e6837ac04c986289bd4c1e754e2d5092bc9dea7a27bb7ad906976bd376f1df
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.