Instructions to use lhong4759/4b829bbc-a40e-41e4-baef-fa38b03b8069 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use lhong4759/4b829bbc-a40e-41e4-baef-fa38b03b8069 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, "lhong4759/4b829bbc-a40e-41e4-baef-fa38b03b8069") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7632ba728dbda229cfe26c5fa0363cfb090521b972d711bea31e396d3892720b
- Size of remote file:
- 83.9 MB
- SHA256:
- 156760f0a8661824062103144a2896ca860fb3cd82fe8af3d5f7e3de8125839a
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