Instructions to use chainyo/alpaca-lora-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use chainyo/alpaca-lora-7b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("decapoda-research/llama-7b-hf") model = PeftModel.from_pretrained(base_model, "chainyo/alpaca-lora-7b") - Notebooks
- Google Colab
- Kaggle
fix: LlaMATokenizer -> LlamaTokenizer
#1
by shionhonda - opened
It's very confusing, but in transformers >= 4.28.0, it is spelled as "Llama" rather than "LlaMA" as in:
https://github.com/huggingface/transformers/blob/32ff06403d48fa018a33ccab02a5f9d3eb8b078b/src/transformers/__init__.py#L4320
Thanks for your contribution!
chainyo changed pull request status to merged