Instructions to use aleegis/b79e2d3f-8088-470b-9713-b9ec3fb3215a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use aleegis/b79e2d3f-8088-470b-9713-b9ec3fb3215a with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-4B-Base") model = PeftModel.from_pretrained(base_model, "aleegis/b79e2d3f-8088-470b-9713-b9ec3fb3215a") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e2fc88000baa9e2a03bb3078fd6766584638653a6e26822010f7705b89a1491c
- Size of remote file:
- 7.16 kB
- SHA256:
- ae2f80b57d94f278467008f794e8740b768c7e0c9d8ee79bd4ea24074e4132d2
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