Instructions to use knatware/knat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use knatware/knat with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("sshleifer/tiny-gpt2") model = PeftModel.from_pretrained(base_model, "knatware/knat") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 39232f762546f431bdd8042837e7d66f5d37a0b366d9f6b5d4cd60dfac8f5b5c
- Size of remote file:
- 3.56 MB
- SHA256:
- 311f7262f89ffe8757683fda3c081a5cac5a885dc311264791a17d2a18499a4f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.