Instructions to use eeeebbb2/95792e15-452c-42bb-aebf-6447a85640be with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use eeeebbb2/95792e15-452c-42bb-aebf-6447a85640be with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Xenova/tiny-random-Phi3ForCausalLM") model = PeftModel.from_pretrained(base_model, "eeeebbb2/95792e15-452c-42bb-aebf-6447a85640be") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- af56bf97aae907e1628ade1f4c22e696099394d7f61c49ac459b8ed5f64374c2
- Size of remote file:
- 6.84 kB
- SHA256:
- a4425d432199ec6b568e339ed888a9fbf72cd66f992a2c69758e38b51e432254
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