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
| 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. | |