Instructions to use eeeebbb2/a50c5de4-9953-4b89-a143-0264a3a50a7c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use eeeebbb2/a50c5de4-9953-4b89-a143-0264a3a50a7c with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-1.5B-Instruct") model = PeftModel.from_pretrained(base_model, "eeeebbb2/a50c5de4-9953-4b89-a143-0264a3a50a7c") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 717a50584892ecc00bbd8c3e81e9a154c3b8b9a0199c57a5160ec878154d8b22
- Size of remote file:
- 15 kB
- SHA256:
- 1b4ea1bb1bf097fb0fa31f72cf7473106b3e65a75a2eb49ec025d1838e5e7f58
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