Instructions to use nhung02/5009e65c-d2a8-47ca-b396-03ce12963728 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhung02/5009e65c-d2a8-47ca-b396-03ce12963728 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("HuggingFaceH4/zephyr-7b-beta") model = PeftModel.from_pretrained(base_model, "nhung02/5009e65c-d2a8-47ca-b396-03ce12963728") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 22797a2b670df05623f727bcfc792d78e005b2a84c5b2c244caa7d3b7d6b2b0c
- Size of remote file:
- 84 MB
- SHA256:
- f31f08627cbcf9afd452b6df15803ff54464f5f6a4116c0305882188087e86e9
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