Instructions to use cragtmp/t3r with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cragtmp/t3r with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/data/LLM/Llama-3.2-11B-Vision-Instruct") model = PeftModel.from_pretrained(base_model, "cragtmp/t3r") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 89758ab098c2f8617cbadd15ba5f6b0dc628ffd257d8132104a54c7419b2b706
- Size of remote file:
- 1.06 kB
- SHA256:
- ccd59e1fdcf1c3ef3f7a750ac57db23dc4fc3bb58615e4e5bf76a0f1955666ce
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.