Instructions to use Technoculture/MT7Bi-alpha with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Technoculture/MT7Bi-alpha with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("epfl-llm/meditron-7b") model = PeftModel.from_pretrained(base_model, "Technoculture/MT7Bi-alpha") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 920a860cbb1a964f7e91b84f226cf007db5848031d7cbfb9d4a33d57194317ec
- Size of remote file:
- 4.8 kB
- SHA256:
- ea0b961a9c8ff316591d8f25471f25101a7a55e20cbef282d902b20386d57bec
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.