Instructions to use chauben/advisorai-llama2-7b-stevens with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use chauben/advisorai-llama2-7b-stevens with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-hf") model = PeftModel.from_pretrained(base_model, "chauben/advisorai-llama2-7b-stevens") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 850d66afacebf65bc7c03ed374285e9c23498b359f5ae095b7b900835ea799a8
- Size of remote file:
- 320 MB
- SHA256:
- 9c52c1a5b49f82f7f0d60bb85fcee621cabe280d9da3b423d06036e8672efc2e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.