Text Generation
PEFT
Safetensors
Turkish
sql
natural-language-to-sql
qlora
lora
rag
turkish
text2sql
conversational
Instructions to use BMinal/sql_coder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use BMinal/sql_coder with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-7B-Instruct") model = PeftModel.from_pretrained(base_model, "BMinal/sql_coder") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5cd63af0e56a88b1bb6bb9d88e5f29350872c1f986792f184a12621f55b92fca
- Size of remote file:
- 14.6 kB
- SHA256:
- a9f0c7f0c9912ba4bfb8cd3de61fa26bae7416b96e038485395dea1e6cf906e5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.