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:
- b4bff17159b553dd23afdb2a8f93df4f9223ee1af07de6d449813028dc563435
- Size of remote file:
- 6.71 kB
- SHA256:
- 2b84fa0d72df2ecf3eeaea93a8b10e7465eba8a318a6c538bf4d50c8795f5163
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