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
File size: 1,268 Bytes
7de68d2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | # Third-party notices
The inference scripts use the packages below, installed separately by the setup commands. These packages are not bundled in this repository. The requirements match [requirements.txt](requirements.txt).
The links identify upstream project licenses. Installed distributions and their dependencies retain their own licenses and notices. For version ranges, consult the license files supplied with the installed version.
| Requirement | Upstream license |
| --- | --- |
| `vllm==0.24.0` | [Apache-2.0](https://github.com/vllm-project/vllm/blob/v0.24.0/LICENSE) |
| `transformers==5.8.1` | [Apache-2.0](https://github.com/huggingface/transformers/blob/v5.8.1/LICENSE) |
| `qwen-vl-utils==0.0.14` | [Apache-2.0](https://github.com/QwenLM/Qwen3-VL/blob/main/LICENSE) |
| `decord==0.6.0` | [Apache-2.0](https://github.com/dmlc/decord/blob/v0.6.0/LICENSE) |
| `av>=15` | [BSD-3-Clause](https://github.com/PyAV-Org/PyAV/blob/main/LICENSE.txt) |
| `numpy<3` | [BSD-3-Clause](https://github.com/numpy/numpy/blob/main/LICENSE.txt) |
| `Pillow>=11,<13` | [PIL Software License (MIT-CMU)](https://github.com/python-pillow/Pillow/blob/main/LICENSE) |
| `huggingface_hub>=1.0` | [Apache-2.0](https://github.com/huggingface/huggingface_hub/blob/main/LICENSE) |
|