Instructions to use tarabukinivan/685b22dd-73f7-49e8-b1e5-2d833ca87b3a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tarabukinivan/685b22dd-73f7-49e8-b1e5-2d833ca87b3a with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("HuggingFaceH4/tiny-random-LlamaForCausalLM") model = PeftModel.from_pretrained(base_model, "tarabukinivan/685b22dd-73f7-49e8-b1e5-2d833ca87b3a") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d0c70645cc25909c88511451df5054962b7bd073072007bb423750c875219dfe
- Size of remote file:
- 6.71 kB
- SHA256:
- caf33c94dce4adc1574cbf9f3a9c4216cb9e4f5357b879cf3f703d4e4b69a80e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.