Instructions to use bwreeves/bloom-7b1-lora-tagger with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use bwreeves/bloom-7b1-lora-tagger with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("bigscience/bloom-1b7") model = PeftModel.from_pretrained(base_model, "bwreeves/bloom-7b1-lora-tagger") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7badf183ba06276d4b1bd3541201f2e94ce65cd9305a088b0ec3f429cf084dd4
- Size of remote file:
- 12.6 MB
- SHA256:
- da6ea8b2baa0de127ce34e3f95edec69681693f11483a36cc3138315e73f6575
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.