Instructions to use dimasik1987/bfd75200-f9fc-4217-824f-eb6aa1a4f9a2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik1987/bfd75200-f9fc-4217-824f-eb6aa1a4f9a2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("garage-bAInd/Camel-Platypus2-70B") model = PeftModel.from_pretrained(base_model, "dimasik1987/bfd75200-f9fc-4217-824f-eb6aa1a4f9a2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b55b6fc113687c1b2191b25d48bae3a585620185873f169d4b0444be8f5f7539
- Size of remote file:
- 1.66 GB
- SHA256:
- b70838d309161c0718fa18418baa76454e514c5a1c00ab925f50f80a6946673b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.