Instructions to use dada22231/d9b72381-1ad7-4fa7-9d6b-670f1c0cfa90 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/d9b72381-1ad7-4fa7-9d6b-670f1c0cfa90 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-Math-1.5B") model = PeftModel.from_pretrained(base_model, "dada22231/d9b72381-1ad7-4fa7-9d6b-670f1c0cfa90") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 957242f794a6075298633ba206cf5c80c03a8230d5c92f4081c11f04db1d231e
- Size of remote file:
- 15 kB
- SHA256:
- 2ac20e59203124c89cbcbae912a3e1b2b1c32a94a28d8fff37f095e3aac9c110
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