Text Classification
Transformers
PyTorch
TensorBoard
ONNX
Safetensors
English
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use usvsnsp/code-vs-nl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use usvsnsp/code-vs-nl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="usvsnsp/code-vs-nl")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("usvsnsp/code-vs-nl") model = AutoModelForSequenceClassification.from_pretrained("usvsnsp/code-vs-nl") - Notebooks
- Google Colab
- Kaggle
ONNX-converted version of the model
#3
by asofter - opened
We decided to add this model for the Code Scanner in llm-guard with your model.
To have faster inference, we use ONNX models converted using Optimum from HuggingFace.
Example of the repo with ONNX built-in: https://huggingface.co/laiyer/deberta-v3-base-prompt-injection
Similar PR: https://huggingface.co/philomath-1209/programming-language-identification/discussions/1
usvsnsp changed pull request status to merged