Instructions to use nblinh63/f7c7e844-5bfb-4d03-8f00-aebcbd671838 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nblinh63/f7c7e844-5bfb-4d03-8f00-aebcbd671838 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-14B-Instruct") model = PeftModel.from_pretrained(base_model, "nblinh63/f7c7e844-5bfb-4d03-8f00-aebcbd671838") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 09ad995611b9abd677ce1949dcfef5156143c4d2183741af4184720686538fe1
- Size of remote file:
- 6.78 kB
- SHA256:
- 717693a35810f8b6d41043834ee611ce5c246deba5373eaf5a14e9c6eadc0cd0
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