Instructions to use beast33/ca1e2a2f-e98c-4d4d-b512-67e8198b14f2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use beast33/ca1e2a2f-e98c-4d4d-b512-67e8198b14f2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-1.1-2b-it") model = PeftModel.from_pretrained(base_model, "beast33/ca1e2a2f-e98c-4d4d-b512-67e8198b14f2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a196a0187f9456194d38da4bb2d835f989d1b6265326f93b87095971a0c27f57
- Size of remote file:
- 314 MB
- SHA256:
- e8f21ead1f998e28695d0fe9b9bc95f61cb508a6c49d3466475bc8249d5273d6
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