Instructions to use abhilash13/sql_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use abhilash13/sql_model with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/qwen2.5-7b-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "abhilash13/sql_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 21b3ed9a836fd73e7dd73c777c5aacf36844a89b90b79267d9b2be558895e148
- Size of remote file:
- 162 MB
- SHA256:
- fd0376424c06b44f68bc66c7e1a31e6a32b5f630115aa72cade30bd143eba011
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.