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 model_weights.pt from sujalgawas/code-bert-python: direct link, hf CLI and curl.
- Browser
- Download file 500 MB
-
https://huggingface.co/sujalgawas/code-bert-python/resolve/1af6f96adb621513df5fe15e2e7c96289a7a9c3e/model_weights.pt
- Command line
-
hf download hf://sujalgawas/code-bert-python@1af6f96adb621513df5fe15e2e7c96289a7a9c3e/model_weights.pt
-
curl -L -o model_weights.pt https://huggingface.co/sujalgawas/code-bert-python/resolve/1af6f96adb621513df5fe15e2e7c96289a7a9c3e/model_weights.pt
500 MB
- Xet hash:
- 22bcd46243c375194aea679ae84f2f94b3649eab6ce65519c4ae4f84c9896249
- Size of remote file:
- 500 MB
- SHA256:
- 5908bf6434ef1637a2af392916c8b68dd021c4c679bba8aebd50896744aa5998
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