Instructions to use CreatorPhan/Bloomz_lora_answer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use CreatorPhan/Bloomz_lora_answer with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("bigscience/bloomz-3b") model = PeftModel.from_pretrained(base_model, "CreatorPhan/Bloomz_lora_answer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 57ed524c2ee3f13f243d98f5d1273b9fd0c3f82b1e0141d6011515406fcdde0d
- Size of remote file:
- 14.5 MB
- SHA256:
- 85b00d7db4df5df2e3f01cacc3feda246002a672f3356eec7f4b04a22eb0dfbe
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.