Instructions to use hipnologo/llama3.2-1B-qlora-churn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use hipnologo/llama3.2-1B-qlora-churn with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-1B-Instruct") model = PeftModel.from_pretrained(base_model, "hipnologo/llama3.2-1B-qlora-churn") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c7566c5ea879e69ed9ca86c31ad5f8cc4d55fdb8795d4844ed8440889e586f6a
- Size of remote file:
- 3.42 MB
- SHA256:
- 9c3fddca83438c8679c4bbc1dad28d6b5825a1917b02418366b6819ac417f418
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