Instructions to use nhung03/a44e4972-db81-4385-8f30-0ee799009e4e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhung03/a44e4972-db81-4385-8f30-0ee799009e4e with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-7B-Instruct") model = PeftModel.from_pretrained(base_model, "nhung03/a44e4972-db81-4385-8f30-0ee799009e4e") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 23e3764781e4cbdeb9a2f090bce5fd826dd2734f4413b34debf423baa682f018
- Size of remote file:
- 80.8 MB
- SHA256:
- 6bdcccd9852489049b8a90ffb9b86c1fe62dfa701eaa04784ec5ca654aec6c20
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