Instructions to use salma-alashry/starcoder2-7b_AR2SQL_RAG1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use salma-alashry/starcoder2-7b_AR2SQL_RAG1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("salma-alashry/starcoder2-7b_AR2SQL_RAG1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from salma-alashry/starcoder2-7b_AR2SQL_RAG1: direct link, hf CLI and curl.
- Browser
- Download file 5.69 kB
-
https://huggingface.co/salma-alashry/starcoder2-7b_AR2SQL_RAG1/resolve/main/training_args.bin
- Command line
-
hf download hf://salma-alashry/starcoder2-7b_AR2SQL_RAG1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/salma-alashry/starcoder2-7b_AR2SQL_RAG1/resolve/main/training_args.bin
5.69 kB
- Xet hash:
- 565d3d4e471da3593af6d2d09f046cb7485268f58f2be87fe7758a1deda35f1c
- Size of remote file:
- 5.69 kB
- SHA256:
- 7a9b78ad99991f665725a8139fd2cb9306081541ba8f563b1c16a4703d5c2ef7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.