Instructions to use sujalgawas/code-bert-python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sujalgawas/code-bert-python with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="sujalgawas/code-bert-python")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sujalgawas/code-bert-python") model = AutoModel.from_pretrained("sujalgawas/code-bert-python", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5b5c385c7a62c0ff0a3746a34f518c93dafd607f42de8735155489e351921264
- Size of remote file:
- 500 MB
- SHA256:
- e9322eed5d552810b8432fbcf097fd9d198aca34600325dc1f72d919e5a3129b
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