Instructions to use 1-lock/8ec787cb-a9c5-47f2-983d-3d13a9372fe7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use 1-lock/8ec787cb-a9c5-47f2-983d-3d13a9372fe7 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Vikhrmodels/Vikhr-7B-instruct_0.4") model = PeftModel.from_pretrained(base_model, "1-lock/8ec787cb-a9c5-47f2-983d-3d13a9372fe7") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 682337c3baddc03e5eab8cf961c8d74c6f1ee89fe627e5bb7d523df22da911be
- Size of remote file:
- 336 MB
- SHA256:
- 6c696cab0a3d3a6350c331a2fa51b164096d09045d83c85832605ebb6c37a08a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.