Instructions to use eeeebbb2/2db455ba-c61d-4cbc-8b93-680e1bb1d782 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use eeeebbb2/2db455ba-c61d-4cbc-8b93-680e1bb1d782 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0") model = PeftModel.from_pretrained(base_model, "eeeebbb2/2db455ba-c61d-4cbc-8b93-680e1bb1d782") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3f61d6712e686eba7504e524c0e2a9abee9b47893b29fe62af056f6afa424cde
- Size of remote file:
- 336 MB
- SHA256:
- a20307749b453db8fa0778403258055c3a8943cd6d91c316bed53a3ee43501d1
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