Instructions to use gotzmann/1SV52 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use gotzmann/1SV52 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Meta-Llama-3.1-8B-Instruct") model = PeftModel.from_pretrained(base_model, "gotzmann/1SV52") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 72d586c8484869adfe7dd8f5bad0591524693f477ef01ed77d6fde3eef5d54cf
- Size of remote file:
- 1.34 GB
- SHA256:
- 3d38c1012de188046fda506f2ea9623297f2c5470edf9e0ba372960f286b3cfb
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