Instructions to use azg-azg/SQLBert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use azg-azg/SQLBert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="azg-azg/SQLBert")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("azg-azg/SQLBert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from azg-azg/SQLBert: direct link, hf CLI and curl.
- Browser
- Download file 503 MB
-
https://huggingface.co/azg-azg/SQLBert/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://azg-azg/SQLBert@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/azg-azg/SQLBert/resolve/refs%2Fpr%2F1/pytorch_model.bin
503 MB
- Xet hash:
- a37348a0fb30cb2956725d08bafcbd12e6f8925627ae5ba32923e920fe737db7
- Size of remote file:
- 503 MB
- SHA256:
- ad505f93f984b590a7552cc3f1d5d3883c066af2b2ea1849fb7733adacabb07d
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