Instructions to use Shengkun/llama2-mpt-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Shengkun/llama2-mpt-instruct 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, "Shengkun/llama2-mpt-instruct") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bdb0b572237238d78713eadaf321e386beefad0448efe2d319bdf7045cba9eaf
- Size of remote file:
- 80.1 MB
- SHA256:
- 634caac31d94073fa65b61417d0a1942f4f1dbf965156387c479fe271379c3e4
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