Instructions to use luckjsg/fbc9aeb3-7113-4701-9ac2-fa460b20cfcb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use luckjsg/fbc9aeb3-7113-4701-9ac2-fa460b20cfcb with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Hermes-2-Pro-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "luckjsg/fbc9aeb3-7113-4701-9ac2-fa460b20cfcb") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7597d3eaffb6eb13b53d97c089a9df4c3a4b45ee5dfc962b790603a999c7a763
- Size of remote file:
- 1.34 GB
- SHA256:
- a2b44fa6e3c1fa052a85d4cc3e0ae982349fdafdc62ea8a14e887fba29717f46
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