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")# pip install -U transformers accelerate # 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
Download model.safetensors from hamzab/codebert_code_search: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/hamzab/codebert_code_search/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hamzab/codebert_code_search@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hamzab/codebert_code_search/resolve/refs%2Fpr%2F1/model.safetensors
499 MB
- Xet hash:
- c93fd8907f5526a0fc4b3befa5874af543930d8a07c21f58d256a7f49f82af30
- Size of remote file:
- 499 MB
- SHA256:
- dcc9fe37ba2305a0e3ebfee52533865bde4b6827c0639946660ea0c14b4830c5
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