Instructions to use shreyash-pandey-katni/SQLForge-Mistral-7B-QLoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use shreyash-pandey-katni/SQLForge-Mistral-7B-QLoRA with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.3") model = PeftModel.from_pretrained(base_model, "shreyash-pandey-katni/SQLForge-Mistral-7B-QLoRA") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8fe54b736866772fd51e4745ea65863d29d5918a87331c25042bb4e951b4fd01
- Size of remote file:
- 1.06 kB
- SHA256:
- f21f56ea6967f07ea25ea6cab60984f014c7de13161f7c73c01877d778622b09
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.