Text Classification
Transformers
PyTorch
Safetensors
English
bert
nlp
code
classification
text-embeddings-inference
Instructions to use vishnun/codenlbert-sm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vishnun/codenlbert-sm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vishnun/codenlbert-sm")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vishnun/codenlbert-sm") model = AutoModelForSequenceClassification.from_pretrained("vishnun/codenlbert-sm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 24ce86260b6fe023e9a50145f95e9a692a39f983738693e7913ed10c6cf6e814
- Size of remote file:
- 115 MB
- SHA256:
- e12b699df73c509f1721c40a5727559b621c2e17349565c9b12dd61c27245bfa
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