Text Classification
Transformers
Safetensors
code
roberta
codebert
vulnerability-detection
cybersecurity
software-security
static-analysis
text-embeddings-inference
Instructions to use Khansa-saAI-29/final-codebert-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Khansa-saAI-29/final-codebert-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Khansa-saAI-29/final-codebert-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Khansa-saAI-29/final-codebert-model") model = AutoModelForSequenceClassification.from_pretrained("Khansa-saAI-29/final-codebert-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5fe02c2fed9e54541b32e6e94bdbf2549c584d7328bc6f62b2f2ac34ad693689
- Size of remote file:
- 499 MB
- SHA256:
- c2bc2bc5b7c90e2a6754a1f223e9a92f3c441f6ef4de59f713ec5b31a1eaebda
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