Instructions to use dzanbek/24d061ec-79e8-4537-b433-d2c4dd786ac2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dzanbek/24d061ec-79e8-4537-b433-d2c4dd786ac2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/tinyllama") model = PeftModel.from_pretrained(base_model, "dzanbek/24d061ec-79e8-4537-b433-d2c4dd786ac2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bbaeebe1496c0cc0def1b682f9edb0f1c5cc36d861dcee1b211ac70585b97700
- Size of remote file:
- 6.78 kB
- SHA256:
- 18292e52d9248f37f68a2acbf7c759f0d8fcc837714dc86062f0c663ac1af0af
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