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:
- 508ff1a8c0d44b1a2c4b05eaef40564083f7f4fc73f1bb13615e0897f27cef0a
- Size of remote file:
- 336 MB
- SHA256:
- 7fbeb513402b1ce167978a7e92e5dc2d2a503b0b82c1a3686d4f78d3590861d1
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