Instructions to use jmcasares/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 jmcasares/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, "jmcasares/code-llama-7b-text-to-sql") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec8dbf77e03db302c5b6d9aed8248e086e39dda6771309c36a930c147f73a80c
- Size of remote file:
- 4.73 kB
- SHA256:
- 3408093c151b19b1a48ea13e476ac3919f2492dbc4083be77c0ee46c955b2c02
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.