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:
- b9f959e326449dcc73f6387adbb9e83dd3d4e8175507babe275666c1c4fe3971
- Size of remote file:
- 6.78 kB
- SHA256:
- 5e11edbf3678cd3fe22b3202bc734009cf41e21eeb68bd31e46cf7a67b6d6abd
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