Instructions to use eeeebbb2/f30106c8-08a4-41b0-a05c-39ceb3d03279 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use eeeebbb2/f30106c8-08a4-41b0-a05c-39ceb3d03279 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM-135M-Instruct") model = PeftModel.from_pretrained(base_model, "eeeebbb2/f30106c8-08a4-41b0-a05c-39ceb3d03279") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1b693b56c5cd233c1500d02402f053e4bb8b0222c539f9d8ad5e95056669ab52
- Size of remote file:
- 39.1 MB
- SHA256:
- 95e67d7fccb2c74f21a5b1dab5d8d37973a2fc0b6d766c6a33271e3a0af76c00
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