Text Classification
Transformers
Safetensors
English
code
code-classification
programming-language
codebert
xgboost
random-forest
gradient-boosting
ensemble
machine-learning
Instructions to use yashodhajayasinghe/nexar-quantum-language-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yashodhajayasinghe/nexar-quantum-language-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yashodhajayasinghe/nexar-quantum-language-classifier")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("yashodhajayasinghe/nexar-quantum-language-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 128 Bytes
c83b9b1 | 1 2 3 4 5 6 | {
"codebert": 0.3,
"xgboost": 0.2,
"random_forest": 0.24999999999999997,
"gradient_boosting": 0.24999999999999997
} |