Instructions to use monsterapi/OpenPlatypus_LLAMA2_7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use monsterapi/OpenPlatypus_LLAMA2_7b 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, "monsterapi/OpenPlatypus_LLAMA2_7b") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 596e5f039d8bdfa8676a9282554d8118486b65a295ba994c21999be8baefefd9
- Size of remote file:
- 33.6 MB
- SHA256:
- 431bc80694cb0bf758bdfe33284e92e1fbdc2054d058396a77a1cc790a7fa5f0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.