Video-Text-to-Text
Transformers
Safetensors
qwen3_5
image-text-to-text
robotics
reward-model
vlm
gr00t
system-2
Instructions to use nvidia/Flora-Rewarder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/Flora-Rewarder with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("nvidia/Flora-Rewarder") model = AutoModelForMultimodalLM.from_pretrained("nvidia/Flora-Rewarder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download batch_utils/__init__.py from nvidia/Flora-Rewarder: direct link, hf CLI and curl.
- Browser
- Download file 92 Bytes
-
https://huggingface.co/nvidia/Flora-Rewarder/resolve/refs%2Fpr%2F3/batch_utils/__init__.py
- Command line
-
hf download hf://nvidia/Flora-Rewarder@refs/pr/3/batch_utils/__init__.py
-
curl -L -o __init__.py https://huggingface.co/nvidia/Flora-Rewarder/resolve/refs%2Fpr%2F3/batch_utils/__init__.py
92 Bytes
| """Example inference scripts for the FLORA rewarder: terminal, dense and rubric rewards.""" | |