Instructions to use EdBerg/Baha_9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use EdBerg/Baha_9 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3.1-8B-Instruct") model = PeftModel.from_pretrained(base_model, "EdBerg/Baha_9") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b35d5d6f8edd4ee8d02f58b22d0a50fcd462ee3baba1d2a56508e517ab95ec6c
- Size of remote file:
- 5.43 kB
- SHA256:
- 238beab0e69fe747445dd4aabb17e06e58827280806d4a8bf5d14663395eba70
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.