Instructions to use Amouri28/Qwen3-4B-lora-DBBench_repo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Amouri28/Qwen3-4B-lora-DBBench_repo with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "Amouri28/Qwen3-4B-lora-DBBench_repo") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1a56c284e377031db097ebd22b5c73530cf83b216ce3357fabd68b4deec4c1eb
- Size of remote file:
- 4.97 GB
- SHA256:
- f046c3e73e668320b2785a36003057a329f705305a1e42241cee7a3686f73d24
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