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 config.json from azg-azg/SQLBert: direct link, hf CLI and curl.
- Browser
- Download file 700 Bytes
-
https://huggingface.co/azg-azg/SQLBert/resolve/main/config.json
- Command line
-
hf download hf://azg-azg/SQLBert/config.json
-
curl -L -o config.json https://huggingface.co/azg-azg/SQLBert/resolve/main/config.json
700 Bytes
- Xet hash:
- c6d8a4ac11716062b64ac22385ef146c22c280064a23718883a7acdf9114d5c8
- Size of remote file:
- 700 Bytes
- SHA256:
- a36e9b0cbc7e6419fe79fccfbbfa7131c98631f78744c8523b191e24793dfd9f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.