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")# pip install -U transformers accelerate # 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
Download tokenizer.json from sujalgawas/code-bert-python: direct link, hf CLI and curl.
- Browser
- Download file 3.56 MB
-
https://huggingface.co/sujalgawas/code-bert-python/resolve/1af6f96adb621513df5fe15e2e7c96289a7a9c3e/tokenizer.json
- Command line
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hf download hf://sujalgawas/code-bert-python@1af6f96adb621513df5fe15e2e7c96289a7a9c3e/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/sujalgawas/code-bert-python/resolve/1af6f96adb621513df5fe15e2e7c96289a7a9c3e/tokenizer.json
3.56 MB
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