Instructions to use dada22231/1742bdb8-56c6-43bf-8dd5-c10e8689c3f2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/1742bdb8-56c6-43bf-8dd5-c10e8689c3f2 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, "dada22231/1742bdb8-56c6-43bf-8dd5-c10e8689c3f2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d31f4879700d657684f621b42763ca97c08d130a495df881d0016a743be227a6
- Size of remote file:
- 15 kB
- SHA256:
- fb05c611a3805157dc2d136f20f093e8b4986be1ee53b08311ddcbc2f55da26a
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