Instructions to use masatochi/tuning-0e7533c8-cd9a-4e62-88b6-79aaf3bbe621 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use masatochi/tuning-0e7533c8-cd9a-4e62-88b6-79aaf3bbe621 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Llama-3.2-1B-Instruct") model = PeftModel.from_pretrained(base_model, "masatochi/tuning-0e7533c8-cd9a-4e62-88b6-79aaf3bbe621") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 40e2361cd032ea022f2dfed375539f3883338942b52de8177d080badfbb8e4c6
- Size of remote file:
- 22.6 MB
- SHA256:
- 0f921b72a29ace0197726921e40ad11d425f583227a1d774164200d9304dd6e8
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