Instructions to use Sreenath/SQLM-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Sreenath/SQLM-7B with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2") model = PeftModel.from_pretrained(base_model, "Sreenath/SQLM-7B") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 09a0f61bae00c1d00d5021cb5e0a71aa8b3a5da3377f59bd323714c808c1f4e6
- Size of remote file:
- 4.98 kB
- SHA256:
- bd0042e660eb10435343ffe6ce469dc3aff5a7c8c2832851a4a243588d69970f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.