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/requirements.txt from nvidia/Flora-Rewarder: direct link, hf CLI and curl.
- Browser
- Download file 120 Bytes
-
https://huggingface.co/nvidia/Flora-Rewarder/resolve/main/batch_utils/requirements.txt
- Command line
-
hf download hf://nvidia/Flora-Rewarder/batch_utils/requirements.txt
-
curl -L -o requirements.txt https://huggingface.co/nvidia/Flora-Rewarder/resolve/main/batch_utils/requirements.txt
120 Bytes
| vllm==0.24.0 | |
| transformers==5.8.1 | |
| qwen-vl-utils==0.0.14 | |
| decord==0.6.0 | |
| av>=15 | |
| numpy<3 | |
| Pillow>=11,<13 | |
| huggingface_hub>=1.0 | |