Instructions to use hamzab/codebert_code_search with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hamzab/codebert_code_search with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hamzab/codebert_code_search")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hamzab/codebert_code_search") model = AutoModel.from_pretrained("hamzab/codebert_code_search", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c93fd8907f5526a0fc4b3befa5874af543930d8a07c21f58d256a7f49f82af30
- Size of remote file:
- 499 MB
- SHA256:
- dcc9fe37ba2305a0e3ebfee52533865bde4b6827c0639946660ea0c14b4830c5
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