Instructions to use FloofCat/CDAC-EmoLLMs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use FloofCat/CDAC-EmoLLMs with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("facebook/bart-base") model = PeftModel.from_pretrained(base_model, "FloofCat/CDAC-EmoLLMs") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ee2f986f734fc6dcdaa5fec21dc68b3d4e52d0e6c21bf5a42a496c41cc045007
- Size of remote file:
- 5.05 kB
- SHA256:
- bfd305ced6a772f43c46776ef054645d870c330cb68c23354e4a079252364274
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