Instructions to use shuolucs/UniLayout-Reward with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shuolucs/UniLayout-Reward with Transformers:
# Load model directly from transformers import LlavaLlamaForClass model = LlavaLlamaForClass.from_pretrained("shuolucs/UniLayout-Reward", dtype="auto") - Notebooks
- Google Colab
- Kaggle
metadata
license: other
library_name: transformers
tags:
- llava
- multimodal
- layout-generation
- reward-model
UniLayout-Reward
Reward model checkpoint for UniLayout layout generation research.
Base model: liuhaotian/llava-v1.6-vicuna-7b.
Vision tower: openai/clip-vit-large-patch14-336.
This repository contains the cleaned model config, tokenizer files, and sharded safetensors weights.