Instructions to use kzipa/code-llama-7b-text-to-sql with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kzipa/code-llama-7b-text-to-sql with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("codellama/CodeLlama-7b-hf") model = PeftModel.from_pretrained(base_model, "kzipa/code-llama-7b-text-to-sql") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4e973f12e4ce27e00b4aaf0cac06f4e5c54d1ac60be38f91c4cd9b1067ba68ab
- Size of remote file:
- 4.73 kB
- SHA256:
- 7b7e8ce2059ff06eff7bd6d29fdb134aa5fa882f82a9dccdfcf2b5f64a22c805
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.