Instructions to use ciloku/6d51336a-610c-4dea-8a46-81c927e7a482 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ciloku/6d51336a-610c-4dea-8a46-81c927e7a482 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Yarn-Mistral-7b-64k") model = PeftModel.from_pretrained(base_model, "ciloku/6d51336a-610c-4dea-8a46-81c927e7a482") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1cc95d0b036685eaed16f2a7cc71861461278cc0f1c7f229b93f0ee4f4f2c7b4
- Size of remote file:
- 671 MB
- SHA256:
- 7bb9234bbccb35084e63d5e4fb59b56a6b987398ce6f325ef24a510ae930eace
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