Instructions to use dzanbek/12cec7cb-7cc2-4e1b-a0c3-2944779bd461 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dzanbek/12cec7cb-7cc2-4e1b-a0c3-2944779bd461 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM-1.7B") model = PeftModel.from_pretrained(base_model, "dzanbek/12cec7cb-7cc2-4e1b-a0c3-2944779bd461") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fb09b4029b96114bf058e1497323692c5bee57c07712569a1473d5d61bf220b7
- Size of remote file:
- 145 MB
- SHA256:
- 0aed7a0715768688a159fb694640250bf9a323c9aa923e6665942c3b7566db52
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