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:
- 169e996c996e0517d2c7af8cb59cdf77644ea1b95546161bdc7c25f9657dbba6
- Size of remote file:
- 6.78 kB
- SHA256:
- ae4332b0c7bb600be4390cb451f39d47c902ae7496603762e9848602f95c5e13
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