Instructions to use berkani/text-to-sql-qlora-qwen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use berkani/text-to-sql-qlora-qwen with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-0.6B") model = PeftModel.from_pretrained(base_model, "berkani/text-to-sql-qlora-qwen") - Transformers
How to use berkani/text-to-sql-qlora-qwen with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("berkani/text-to-sql-qlora-qwen", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 047fb6fb74dafdddc051eb170116838d7800960aa1a7b8be327a7d3c1abc4de7
- Size of remote file:
- 11.4 MB
- SHA256:
- b064181fd20c7d19d5613f061552279d7dcbb8210ffde80386e2a9a6ddf996e7
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