Instructions to use inagakimugi/qwen3-4b-sft-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use inagakimugi/qwen3-4b-sft-v3 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, "inagakimugi/qwen3-4b-sft-v3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d8760dd5cf04bebe3495000d644d1e3abadd35080e9ce77deddefbf1267c10e8
- Size of remote file:
- 2.11 GB
- SHA256:
- 67ab6173c7ac53112ec4a353f00e44c554c370fbd694730e7744b1818798a88a
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