Instructions to use dimasik87/5933fc7c-eb40-4e07-ad9d-a841166e2089 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik87/5933fc7c-eb40-4e07-ad9d-a841166e2089 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, "dimasik87/5933fc7c-eb40-4e07-ad9d-a841166e2089") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a352fe74f8091ba09f2d94943c1f1125092248020f4fcb59ce2f1261049dad7
- Size of remote file:
- 73.9 MB
- SHA256:
- ef1ca1ff1e072ffec967a54769a8c1850aa3c5d1980352f8308959b2e4fd9ae6
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