Instructions to use Enoch/Unixcoder-Tuned-Code-Search-Py with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Enoch/Unixcoder-Tuned-Code-Search-Py with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Enoch/Unixcoder-Tuned-Code-Search-Py")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Enoch/Unixcoder-Tuned-Code-Search-Py") model = AutoModel.from_pretrained("Enoch/Unixcoder-Tuned-Code-Search-Py", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from Enoch/Unixcoder-Tuned-Code-Search-Py: direct link, hf CLI and curl.
- Browser
- Download file 504 MB
-
https://huggingface.co/Enoch/Unixcoder-Tuned-Code-Search-Py/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://Enoch/Unixcoder-Tuned-Code-Search-Py@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Enoch/Unixcoder-Tuned-Code-Search-Py/resolve/refs%2Fpr%2F1/model.safetensors
504 MB
- Xet hash:
- 9fb6cb5481683683636c8fc929ad3daec29ab7dd4876266be1892b4fe2c633e7
- Size of remote file:
- 504 MB
- SHA256:
- bd188e2829563f192f890f7a65f6b5bd151547ae78c8ddeeff4509b045c62841
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