Text Classification
Transformers
ONNX
Safetensors
English
roberta
code
programming-language
code-classification
text-embeddings-inference
Instructions to use philomath-1209/programming-language-identification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use philomath-1209/programming-language-identification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="philomath-1209/programming-language-identification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("philomath-1209/programming-language-identification") model = AutoModelForSequenceClassification.from_pretrained("philomath-1209/programming-language-identification") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a6e184eb96e3f67ef4705bdd59ae1e52123a90de861e238335c8ba2ffe47e137
- Size of remote file:
- 4.73 kB
- SHA256:
- 7c48036af989e1b9e4843901c0aae01d2174db734c36980164adf76df423df5f
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