Instructions to use vickarrious/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 vickarrious/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, "vickarrious/code-llama-7b-text-to-sql") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6a3a6c54a3deafa9c872eded3e8fbfc731574bf5f0603d72771bafabb63861a0
- Size of remote file:
- 1.8 GB
- SHA256:
- 5a9d4449679abe1dc79cbe3ca7158b9d12baa869748d51b80aab03ff1ed9b6cb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.