Text Classification
Transformers
PyTorch
JAX
Safetensors
roberta
Text Classification
Transformers
PyTorch
JAX
MSR
English
Inference Endpoints
text-embeddings-inference
Instructions to use starmage520/Coderbert_finetuned_detect_vulnerability_on_MSR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use starmage520/Coderbert_finetuned_detect_vulnerability_on_MSR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="starmage520/Coderbert_finetuned_detect_vulnerability_on_MSR")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("starmage520/Coderbert_finetuned_detect_vulnerability_on_MSR") model = AutoModelForSequenceClassification.from_pretrained("starmage520/Coderbert_finetuned_detect_vulnerability_on_MSR") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a71199f4a4420e0e6fad3836cfe650ec05ec97b8ae5f1eabee3bb5e78bcf9801
- Size of remote file:
- 499 MB
- SHA256:
- 4be1f8759bd1d8c1d57ee9c737709be3f17ef05d851985fd52d438ac39e25d2b
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