Instructions to use hongyeeliu/Control_Summaries_LLaMA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use hongyeeliu/Control_Summaries_LLaMA with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/meta-llama-3.1-8b-instruct-bnb-4bit") model = PeftModel.from_pretrained(base_model, "hongyeeliu/Control_Summaries_LLaMA") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2ea3954d46580c9f7405d86ecdc524765740df559e5ab72384e87cf347ece45b
- Size of remote file:
- 17.2 MB
- SHA256:
- 4012dfe6bbb5c6a7ab05c75bd469c16a78fa811e79378a36b994e4ec010d107b
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