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/examples/jobs.jsonl from nvidia/Flora-Rewarder: direct link, hf CLI and curl.
- Browser
- Download file 384 Bytes
-
https://huggingface.co/nvidia/Flora-Rewarder/resolve/main/batch_utils/examples/jobs.jsonl
- Command line
-
hf download hf://nvidia/Flora-Rewarder/batch_utils/examples/jobs.jsonl
-
curl -L -o jobs.jsonl https://huggingface.co/nvidia/Flora-Rewarder/resolve/main/batch_utils/examples/jobs.jsonl
384 Bytes
| {"id": "episode_0001", "task": "Put the cup on the tray.", "videos": ["videos/episode_0001/left_wrist.mp4", "videos/episode_0001/top.mp4", "videos/episode_0001/right_wrist.mp4"]} | |
| {"id": "episode_0002", "task": "Open the drawer and put the sponge inside.", "videos": ["videos/episode_0002/exterior_left.mp4", "videos/episode_0002/wrist.mp4", "videos/episode_0002/exterior_right.mp4"]} | |