Instructions to use microsoft/codebert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/codebert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="microsoft/codebert-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("microsoft/codebert-base") model = AutoModel.from_pretrained("microsoft/codebert-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from microsoft/codebert-base: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/microsoft/codebert-base/resolve/7d49cad1fa03e1c6d4c12c75bda90a277ea894fb/pytorch_model.bin
- Command line
-
hf download hf://microsoft/codebert-base@7d49cad1fa03e1c6d4c12c75bda90a277ea894fb/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/microsoft/codebert-base/resolve/7d49cad1fa03e1c6d4c12c75bda90a277ea894fb/pytorch_model.bin
499 MB
- Xet hash:
- 80964601258d1d0d5d88fb62399c3adcad808696757cd71394c7ee831265db79
- Size of remote file:
- 499 MB
- SHA256:
- 28b61fd8fa069f6bc966f4cb9572a4026ab2a784fca8fb224020d91b744e32d6
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