Instructions to use HamadaMayu/qwen3-4b-structured-output-lora-v4-2epoch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use HamadaMayu/qwen3-4b-structured-output-lora-v4-2epoch with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-4B-Instruct-2507") model = PeftModel.from_pretrained(base_model, "HamadaMayu/qwen3-4b-structured-output-lora-v4-2epoch") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 23d988fc3d6759eb945f3c2fd4db8b31ac69460c42da6286c5e116e0c5d98c3c
- Size of remote file:
- 529 MB
- SHA256:
- b3237ce4db46fa09af432eb7882f4f6fa5896bd36fb23086a4f8047c7f36e901
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