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:
- 8f557779e8898972670b4834eaf38fec325c1419d1f23d5368028c01fa5077f8
- Size of remote file:
- 6.78 kB
- SHA256:
- 82e199fd6fbe95dd829ac8f734d129d6aeec72049a7615ae9881066f7acffbb2
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