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:
- de72756a94a1d03d9d4ca6eab7ecc26fda7dffe011192d0f585ae0fef190cc1b
- Size of remote file:
- 6.84 kB
- SHA256:
- 414c2421e573fc1d7abaaf8d6b8c1a281c9cb120297a737e52041d43623acff0
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