Instructions to use monsterapi/llama7B_alpaca-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use monsterapi/llama7B_alpaca-lora 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, "monsterapi/llama7B_alpaca-lora") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 324424bbd6a0331cf9d198a298f62680ed3be72c417639f10bbc490514d9d08a
- Size of remote file:
- 16.8 MB
- SHA256:
- b6f00636122db2ca9aa7b60e9d141b27f94f5afef5384294a043c94cef4fd372
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.