Feature Extraction
Transformers
Safetensors
qwen3_vl
worl
nvrm
reward-model
video-reward-model
qwen3-vl
Instructions to use Efficient-Large-Model/WORL-NVRM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Efficient-Large-Model/WORL-NVRM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Efficient-Large-Model/WORL-NVRM")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("Efficient-Large-Model/WORL-NVRM") model = AutoModel.from_pretrained("Efficient-Large-Model/WORL-NVRM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from Efficient-Large-Model/WORL-NVRM: direct link, hf CLI and curl.
- Browser
- Download file 613 Bytes
-
https://huggingface.co/Efficient-Large-Model/WORL-NVRM/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://Efficient-Large-Model/WORL-NVRM/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/Efficient-Large-Model/WORL-NVRM/resolve/main/special_tokens_map.json
613 Bytes
| { | |
| "additional_special_tokens": [ | |
| "<|im_start|>", | |
| "<|im_end|>", | |
| "<|object_ref_start|>", | |
| "<|object_ref_end|>", | |
| "<|box_start|>", | |
| "<|box_end|>", | |
| "<|quad_start|>", | |
| "<|quad_end|>", | |
| "<|vision_start|>", | |
| "<|vision_end|>", | |
| "<|vision_pad|>", | |
| "<|image_pad|>", | |
| "<|video_pad|>" | |
| ], | |
| "eos_token": { | |
| "content": "<|im_end|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "pad_token": { | |
| "content": "<|endoftext|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| } | |
| } | |