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:
- dd571c42bb4465aba46e7bf58e828cdb38b02d0bab4831acd78e1165bf2834fc
- Size of remote file:
- 275 MB
- SHA256:
- 1184bb9bd219d8ed03439fea294e44ccedf3a56517ef156e402b61fb1bcaf518
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