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")# pip install -U transformers accelerate # 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
Download training_args.bin from Khansa-saAI-29/final-codebert-model: direct link, hf CLI and curl.
- Browser
- Download file 5.59 kB
-
https://huggingface.co/Khansa-saAI-29/final-codebert-model/resolve/main/training_args.bin
- Command line
-
hf download hf://Khansa-saAI-29/final-codebert-model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Khansa-saAI-29/final-codebert-model/resolve/main/training_args.bin
5.59 kB
- Xet hash:
- 3f780f09b8ddb12938ea9a2e5dd690f033fbe316632276c367649a769ff7496c
- Size of remote file:
- 5.59 kB
- SHA256:
- 9c1322962343b462a1342564bf220df0e61e07c7c2a63d18a8afc3fedfa5846c
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