Instructions to use nhung03/f10bdf17-9e76-43d8-9e0e-0b65ee5e0e98 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhung03/f10bdf17-9e76-43d8-9e0e-0b65ee5e0e98 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-Coder-7B") model = PeftModel.from_pretrained(base_model, "nhung03/f10bdf17-9e76-43d8-9e0e-0b65ee5e0e98") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1e3f70fc58104f09cf3f938ebdf4f08eef6bf07b6cdfa667126473c612136de7
- Size of remote file:
- 6.78 kB
- SHA256:
- 9116cb3be77cda2009b6540c7581fb7834cf7c2594559a1b8300e4be6247a6b7
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