Instructions to use trangtrannnnn/4ccd6b6d-609c-4b36-b351-87aca3f76e75 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use trangtrannnnn/4ccd6b6d-609c-4b36-b351-87aca3f76e75 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2-0.5B") model = PeftModel.from_pretrained(base_model, "trangtrannnnn/4ccd6b6d-609c-4b36-b351-87aca3f76e75") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a35587f0edb5f3e1a40e9680f968524312f8f72a8db75fa16fafb9adfed23976
- Size of remote file:
- 17.6 MB
- SHA256:
- b3e97936035d2b8aeee749645fd4f32619933828a8ceee924e061b79f46402c6
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