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 PROVENANCE.json from nvidia/Flora-Rewarder: direct link, hf CLI and curl.
- Browser
- Download file 306 Bytes
-
https://huggingface.co/nvidia/Flora-Rewarder/resolve/main/PROVENANCE.json
- Command line
-
hf download hf://nvidia/Flora-Rewarder/PROVENANCE.json
-
curl -L -o PROVENANCE.json https://huggingface.co/nvidia/Flora-Rewarder/resolve/main/PROVENANCE.json
306 Bytes
| { | |
| "schema_version": 2, | |
| "model": "Flora-rewarder-27B", | |
| "selected_step": 1354, | |
| "base_model": "Qwen/Qwen3.5-27B", | |
| "base_revision": "fc05daec18b0a78c049392ed2e771dde82bdf654", | |
| "format": "full model in sharded safetensors", | |
| "checkpoint_storage_dtype": "BF16", | |
| "source_weights_modified": false | |
| } | |