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:
- 47346cef74566129e0c4d389195c982bd4476b6266f35c53cc6c9d96bf6e1c64
- Size of remote file:
- 15 kB
- SHA256:
- 54ad6b18ebac90119de92cc44344e9102f75527c15cddec8a9a1a73157c89d40
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