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.safetensors from sujalgawas/code-bert-python: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/sujalgawas/code-bert-python/resolve/main/model.safetensors
- Command line
-
hf download hf://sujalgawas/code-bert-python/model.safetensors
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curl -L -o model.safetensors https://huggingface.co/sujalgawas/code-bert-python/resolve/main/model.safetensors
499 MB
- Xet hash:
- fbb5b8820c57dcb29571464af1eee99ca4b15864edb16fe5386bbd49927c1049
- Size of remote file:
- 499 MB
- SHA256:
- 545cb43e77f9234af54a20412bbcb1dde08d275bef59220ba66b738bccdd6910
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