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:
- 665976d79796e407dbc4a22ab7c619449952fe7a2d07a3104f2b8d7a6242e27d
- Size of remote file:
- 3.96 kB
- SHA256:
- fb1bb243023642a923d0d09b93f66e328c9dcfb81c4097e2e9a7464ab34f4190
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