Instructions to use daniel40/7ec92e17-18b5-4ab8-b7e8-cc6e5bd29f7e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use daniel40/7ec92e17-18b5-4ab8-b7e8-cc6e5bd29f7e 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, "daniel40/7ec92e17-18b5-4ab8-b7e8-cc6e5bd29f7e") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e7a59a057bbb73fa9da685077fb65ff93d467eadd475f0408191e59be5184875
- Size of remote file:
- 6.78 kB
- SHA256:
- 675bce3be857a1e9cafe344a15e2133ff79be9b0139ecb7356dc603797d8b013
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