Instructions to use adammandic87/02b264b8-3dea-4fc5-931f-554f3ab093ea with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use adammandic87/02b264b8-3dea-4fc5-931f-554f3ab093ea with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2-1.5B-Instruct") model = PeftModel.from_pretrained(base_model, "adammandic87/02b264b8-3dea-4fc5-931f-554f3ab093ea") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d44c74bd1887cbcda3abaa6873bb40d74ad33faab01aee8ab1075bfb8013ea0d
- Size of remote file:
- 37.1 MB
- SHA256:
- 9f9b638053912b5e5cdfae60daed74c083119d89367f4f4ba0bfd2d26abffe0a
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