Instructions to use DevQuasar/analytical_reasoning_Llama-3.2-1B_adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DevQuasar/analytical_reasoning_Llama-3.2-1B_adapter with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Llama-3.2-1B-bnb-4bit") model = PeftModel.from_pretrained(base_model, "DevQuasar/analytical_reasoning_Llama-3.2-1B_adapter") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ffdb57993f720c05af845e02d199ed335cbbff658c676a163f62d8e2a212c2f6
- Size of remote file:
- 5.56 kB
- SHA256:
- 5ee492fe6116a71c16e11c50100e63c2631703abddb7e11e0df67d364222a536
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