Instructions to use Imadken/LLama_dbricks_lamini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Imadken/LLama_dbricks_lamini with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Llama-2-7b-hf") model = PeftModel.from_pretrained(base_model, "Imadken/LLama_dbricks_lamini") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9645605791b578510837bf6a8e8b33196d17960e19d55309add48824eb1999be
- Size of remote file:
- 67.2 MB
- SHA256:
- 2339e18417ef93fde219cee333b62b9dc134c0b4990fed07165837bffe457af7
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