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
- Xet hash:
- a7ebfb22d48ea823d9293bd5729ea85ca6dd8b99e8bbec086272e5293a2e6063
- Size of remote file:
- 268 MB
- SHA256:
- 6a811da718a168bedec50099c926e2506854c477c49e9d91fe66d86f8f09f4b7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.