Instructions to use phungkhaccuong/11f7f0f9-9cf9-46fa-9dca-e2904d14aa99 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use phungkhaccuong/11f7f0f9-9cf9-46fa-9dca-e2904d14aa99 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, "phungkhaccuong/11f7f0f9-9cf9-46fa-9dca-e2904d14aa99") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8b32dbc8d8021a243e483c497f2a1568f144ae13e3b34c6818b27421534308ed
- Size of remote file:
- 30.7 kB
- SHA256:
- 7f5de6917416ad723d2705c427aea166235e59869c541c94c048e9d379d8d04e
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